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\n \n\n \n \n \n \n \n \n RP Scripts — Release 2.0.\n \n \n \n \n\n\n \n Sampaio, M. d. S.\n\n\n \n\n\n\n May 2023.\n \n\n\n\n
\n\n\n\n \n \n \"RPPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Manual{           sampaio2023-rp-scripts,\n    author       = {Sampaio, Marcos da Silva},\n    year         = 2023,\n    title        = {{RP Scripts} --- Release 2.0},\n    month        = {May},\n    url          = {https://marcos.sampaio.me/files/sampaio2023-rp-2.0.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n RP Scripts: Rhythmic Partitioning Scripts, Release 2.0.\n \n \n \n\n\n \n Sampaio, M.\n\n\n \n\n\n\n Available at ˘rlhttps://github.com/msampaio/rpScripts. Accessed on May. 13, 2023, 2023.\n \n\n\n\n
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@Misc{             sampaio2023-rp-scripts-a,\n    author       = {{Sampaio}, {Marcos da Silva}},\n    year         = {2023},\n    title        = {{RP Scripts}: {Rhythmic} {Partitioning} {Scripts},\n                   Release 2.0},\n    howpublished = "Available at \\url{https://github.com/msampaio/rpScripts}.\n                   Accessed on May. 13, 2023"\n}\n\n
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\n \n\n \n \n \n \n \n \n Partitura: A Python Package for Symbolic Music Processing.\n \n \n \n \n\n\n \n Cancino-Chacón, C.; Peter, S. D.; Karystinaios, E.; Foscarin, F.; Grachten, M.; and Widmer, G.\n\n\n \n\n\n\n June 2022.\n arXiv:2206.01071 [cs, eess]\n\n\n\n
\n\n\n\n \n \n \"Partitura:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Misc{             cancino-chacon.ea2022-partitura,\n    author       = {Cancino-Chac{\\'{o}}n, Carlos and Peter, Silvan David and\n                   Karystinaios, Emmanouil and Foscarin, Francesco and\n                   Grachten, Maarten and Widmer, Gerhard},\n    year         = {2022},\n    title        = {Partitura: {A} {Python} {Package} for {Symbolic} {Music}\n                   {Processing}},\n    shorttitle   = {Partitura},\n    url          = {http://arxiv.org/abs/2206.01071},\n    abstract     = {Partitura is a lightweight Python package for handling\n                   symbolic musical information. It provides easy access to\n                   features commonly used in music information retrieval\n                   tasks, like note arrays (lists of timed pitched events)\n                   and 2D piano roll matrices, as well as other score\n                   elements such as time and key signatures, performance\n                   directives, and repeat structures. Partitura can load\n                   musical scores (in MEI, MusicXML, Humdrum **kern, and MIDI\n                   formats), MIDI performances, and score-to-performance\n                   alignments. The package includes some tools for music\n                   analysis, such as automatic pitch spelling, key signature\n                   identification, and voice separation. Partitura is an\n                   open-source project and is available at\n                   https://github.com/CPJKU/partitura/.},\n    language     = {en},\n    urldate      = {2022-07-31},\n    publisher    = {arXiv},\n    month        = jun,\n    note         = {arXiv:2206.01071 [cs, eess]},\n    tags         = {music and computer},\n    keywords     = {Computer Science - Digital Libraries, Computer Science -\n                   Sound, Electrical Engineering and Systems Science - Audio\n                   and Speech Processing}\n}\n\n
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\n Partitura is a lightweight Python package for handling symbolic musical information. It provides easy access to features commonly used in music information retrieval tasks, like note arrays (lists of timed pitched events) and 2D piano roll matrices, as well as other score elements such as time and key signatures, performance directives, and repeat structures. Partitura can load musical scores (in MEI, MusicXML, Humdrum **kern, and MIDI formats), MIDI performances, and score-to-performance alignments. The package includes some tools for music analysis, such as automatic pitch spelling, key signature identification, and voice separation. Partitura is an open-source project and is available at https://github.com/CPJKU/partitura/.\n
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\n \n\n \n \n \n \n \n Melodic Contour and Rhythm as Organizing Principles in Schoenberg's Wind Quintet, Op. 26.\n \n \n \n\n\n \n Carmona, T.\n\n\n \n\n\n\n Ph.D. Thesis, Texas Tech University, 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@PhDThesis{        carmona2022-melodic,\n    author       = {Carmona, Taylor},\n    year         = {2022},\n    title        = {Melodic Contour and Rhythm as Organizing Principles in\n                   Schoenberg's Wind Quintet, Op. 26},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    school       = {Texas Tech University},\n    type         = {Ph.D. Dissertation}\n}\n\n
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\n \n\n \n \n \n \n \n \n Annotating symbolic texture in Piano Music: a formal syntax.\n \n \n \n \n\n\n \n Couturier, L.; Bigo, L.; and Leve, F.\n\n\n \n\n\n\n In pages 8, Saint-Etienne, France, 2022. \n \n\n\n\n
\n\n\n\n \n \n \"AnnotatingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    couturier.ea2022-annotating,\n    author       = {Couturier, Louis and Bigo, Louis and Leve, Florence},\n    year         = {2022},\n    title        = {Annotating symbolic texture in {Piano} {Music}: a formal\n                   syntax},\n    address      = {Saint-Etienne, France},\n    url          = {https://hal.archives-ouvertes.fr/hal-03631151/document},\n    abstract     = {Symbolic texture describes how sounding components are\n                   organized in a musical score. Along with other high-level\n                   musical components such as melody, harmony or rhythm,\n                   symbolic texture has a significant impact on the\n                   structure and the style of a musical piece. In this\n                   article, we present a syntax to describe compositional\n                   texture in the specific case of Western classical piano\n                   music. The syntax is expressive and flexible, unifying\n                   into a single text label information about density,\n                   diversity, musical function and note relationships in\n                   distinct textural units. The formal definition of the\n                   syntax enables its parsing and computational processing,\n                   opening promising perspectives in computeraided music\n                   analysis and composition. We provide an implementation to\n                   parse and manipulate textural labels as well as a bestiary\n                   of annotated examples of textural configurations.},\n    language     = {en},\n    keywords     = {Computational Musicology},\n    pages        = {8}\n}\n\n
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\n Symbolic texture describes how sounding components are organized in a musical score. Along with other high-level musical components such as melody, harmony or rhythm, symbolic texture has a significant impact on the structure and the style of a musical piece. In this article, we present a syntax to describe compositional texture in the specific case of Western classical piano music. The syntax is expressive and flexible, unifying into a single text label information about density, diversity, musical function and note relationships in distinct textural units. The formal definition of the syntax enables its parsing and computational processing, opening promising perspectives in computeraided music analysis and composition. We provide an implementation to parse and manipulate textural labels as well as a bestiary of annotated examples of textural configurations.\n
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\n \n\n \n \n \n \n \n \n A Dataset of Symbolic Texture Annotations in Mozart Piano Sonatas.\n \n \n \n \n\n\n \n Couturier, L.; Bigo, L.; and Leve, F.\n\n\n \n\n\n\n . December 2022.\n Publisher: Zenodo\n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@Article{          couturier.ea2022-dataset,\n    author       = {Couturier, Louis and Bigo, Louis and Leve, Florence},\n    year         = {2022},\n    title        = {A {Dataset} of {Symbolic} {Texture} {Annotations} in\n                   {Mozart} {Piano} {Sonatas}},\n    copyright    = {Creative Commons Attribution 4.0 International, Open\n                   Access},\n    url          = {https://zenodo.org/record/7316712},\n    doi          = {10.5281/ZENODO.7316712},\n    abstract     = {Musical scores are generally analyzed under different\n                   aspects, notably melody, harmony, rhythm, but also through\n                   their texture, although this last concept is arguably more\n                   delicate to formalize. Symbolic texture depicts how\n                   sounding components are organized in the score. It\n                   outlines the density of elements, their heterogeneity,\n                   role and interactions. In this paper, we release a set of\n                   manual annotations for each bar of 9 movements among early\n                   piano sonatas by W. A. Mozart, totaling 1164 labels that\n                   follow a syntax dedicated to piano score texture. A\n                   quantitative analysis of the annotations highlights some\n                   characteristic textural features in the corpus. In\n                   addition, we present and release the implementation of\n                   low-level descriptors of symbolic texture, that are\n                   preliminary experimented for textural elements prediction.\n                   The annotations and the descriptors offer promising\n                   applications in computer-assisted music analysis and\n                   composition.},\n    language     = {en},\n    urldate      = {2023-02-23},\n    month        = dec,\n    note         = {Publisher: Zenodo},\n    keywords     = {ismir, ismir2022}\n}\n\n
\n
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\n Musical scores are generally analyzed under different aspects, notably melody, harmony, rhythm, but also through their texture, although this last concept is arguably more delicate to formalize. Symbolic texture depicts how sounding components are organized in the score. It outlines the density of elements, their heterogeneity, role and interactions. In this paper, we release a set of manual annotations for each bar of 9 movements among early piano sonatas by W. A. Mozart, totaling 1164 labels that follow a syntax dedicated to piano score texture. A quantitative analysis of the annotations highlights some characteristic textural features in the corpus. In addition, we present and release the implementation of low-level descriptors of symbolic texture, that are preliminary experimented for textural elements prediction. The annotations and the descriptors offer promising applications in computer-assisted music analysis and composition.\n
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\n \n\n \n \n \n \n \n Computational Similarity Models of Portuguese Folk Melodies Using Hierarchical Reduction.\n \n \n \n\n\n \n Diogo, D. F.\n\n\n \n\n\n\n Master's thesis, Universidade do Porto, 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@MastersThesis{    diogo2022-computational,\n    author       = {Diogo, Daniel Ferreira},\n    year         = {2022},\n    title        = {Computational {Similarity} {Models} of {Portuguese}\n                   {Folk} {Melodies} {Using} {Hierarchical} {Reduction}},\n    language     = {en},\n    tags         = {computational musicology},\n    school       = {Universidade do Porto}\n}\n\n
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\n \n\n \n \n \n \n \n \n Smart-Median: A New Real-Time Algorithm for Smoothing Singing Pitch Contours.\n \n \n \n \n\n\n \n Faghih, B.; and Timoney, J.\n\n\n \n\n\n\n Applied Sciences, 12(14): 7026. July 2022.\n \n\n\n\n
\n\n\n\n \n \n \"Smart-Median:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          faghih.ea2022-smart-median,\n    author       = {Faghih, Behnam and Timoney, Joseph},\n    year         = {2022},\n    title        = {Smart-{Median}: {A} {New} {Real}-{Time} {Algorithm} for\n                   {Smoothing} {Singing} {Pitch} {Contours}},\n    volume       = {12},\n    issn         = {2076-3417},\n    shorttitle   = {Smart-{Median}},\n    url          = {https://www.mdpi.com/2076-3417/12/14/7026},\n    doi          = {10.3390/app12147026},\n    abstract     = {Pitch detection is usually one of the fundamental steps\n                   in audio signal processing. However, it is common for\n                   pitch detectors to estimate a portion of the fundamental\n                   frequencies incorrectly, especially in real-time\n                   environments and when applied to singing. Therefore, the\n                   estimated pitch contour usually has errors. To remove\n                   these errors, a contour smoother algorithm should be\n                   employed. However, because none of the current\n                   contour-smoother algorithms has been explicitly designed\n                   to be applied to contours generated from singing, they are\n                   often unsuitable for this purpose. Therefore, this article\n                   aims to introduce a new smoother algorithm that rectifies\n                   this. The proposed smoother algorithm is compared with 15\n                   other smoother algorithms over approximately 2700 pitch\n                   contours. Four metrics were used for the comparison.\n                   According to all the metrics, the proposed algorithm could\n                   smooth the contours more accurately than other algorithms.\n                   A distinct conclusion is that smoother algorithms should\n                   be designed according to the contour type and the result's\n                   final applications.},\n    language     = {en},\n    number       = {14},\n    urldate      = {2022-07-13},\n    journal      = {Applied Sciences},\n    month        = jul,\n    keywords     = {music contour},\n    pages        = {7026}\n}\n\n
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\n Pitch detection is usually one of the fundamental steps in audio signal processing. However, it is common for pitch detectors to estimate a portion of the fundamental frequencies incorrectly, especially in real-time environments and when applied to singing. Therefore, the estimated pitch contour usually has errors. To remove these errors, a contour smoother algorithm should be employed. However, because none of the current contour-smoother algorithms has been explicitly designed to be applied to contours generated from singing, they are often unsuitable for this purpose. Therefore, this article aims to introduce a new smoother algorithm that rectifies this. The proposed smoother algorithm is compared with 15 other smoother algorithms over approximately 2700 pitch contours. Four metrics were used for the comparison. According to all the metrics, the proposed algorithm could smooth the contours more accurately than other algorithms. A distinct conclusion is that smoother algorithms should be designed according to the contour type and the result's final applications.\n
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\n \n\n \n \n \n \n \n PARSEMAT: Parseme Toolbox Software Package v. 0.9 Beta.\n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n Available at ˘rlhttps://pauxy.net/parsemat-3/. Accessed on Dec. 16, 2022, 2022.\n \n\n\n\n
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@Misc{             gentil-nunes2022-parsemat,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2022},\n    title        = {{PARSEMAT}: Parseme Toolbox Software Package v. 0.9\n                   Beta},\n    howpublished = "Available at \\url{https://pauxy.net/parsemat-3/}.\n                   Accessed on Dec. 16, 2022"\n}\n\n
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\n \n\n \n \n \n \n \n Rhetorical Pattern Finding.\n \n \n \n\n\n \n Gómez, F.; Tizón, M.; Arronte, A.; and Padilla, V.\n\n\n \n\n\n\n International Journal of Interactive Multimedia and Artificial Intelligence,8. 2022.\n \n\n\n\n
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@Article{          gomez.ea2022-rhetorical,\n    author       = {G\\'{o}mez, Francisco and Tiz\\'{o}n, Manuel and Arronte,\n                   Aitor and Padilla, V\\'{i}ctor},\n    year         = {2022},\n    title        = {Rhetorical {Pattern} {Finding}},\n    abstract     = {In this paper, we research rhetorical patterns from a\n                   musicological and computational standpoint. First, a\n                   theoretical examination of what constitutes a rhetorical\n                   pattern is conducted. Out of that examination, which\n                   includes primary sources and the study of the main\n                   composers, a formal definition of rhetorical patterns is\n                   proposed. Among the rhetorical figures, a set of imitative\n                   rhetorical figures is selected for our study, namely,\n                   epizeuxis, palilogy, synonymia, and polyptoton. Next, we\n                   design a computational model of the selected rhetorical\n                   patterns to automatically find those patterns in a corpus\n                   consisting of masses by Renaissance composer Tom\\'{a}s\n                   Luis de Victoria. In order to have a ground truth with\n                   which to test out our model, a group of experts manually\n                   annotated the rhetorical patterns. To deal with the\n                   problem of reaching a consensus on the annotations, a\n                   four-round Delphi method was followed by the annotators.\n                   The rhetorical patterns found by the annotators and by the\n                   algorithm are compared and their differences discussed.\n                   The algorithm reports almost all the patterns annotated by\n                   the experts and some additional patterns. The algorithm\n                   reports almost all the patterns annotated by the experts\n                   (recall: 98.11\\%) and some additional patterns (precision:\n                   71.73\\%). These patterns correspond to rhetorical patterns\n                   within other rhetorical patterns, which were overlooked by\n                   the annotators on the basis of their contextual knowledge.\n                   These results pose issues as to how to integrate that\n                   contextual knowledge into the computational model.},\n    language     = {en},\n    journal      = {International Journal of Interactive Multimedia and\n                   Artificial Intelligence},\n    pages        = {8}\n}\n\n
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\n In this paper, we research rhetorical patterns from a musicological and computational standpoint. First, a theoretical examination of what constitutes a rhetorical pattern is conducted. Out of that examination, which includes primary sources and the study of the main composers, a formal definition of rhetorical patterns is proposed. Among the rhetorical figures, a set of imitative rhetorical figures is selected for our study, namely, epizeuxis, palilogy, synonymia, and polyptoton. Next, we design a computational model of the selected rhetorical patterns to automatically find those patterns in a corpus consisting of masses by Renaissance composer Tomás Luis de Victoria. In order to have a ground truth with which to test out our model, a group of experts manually annotated the rhetorical patterns. To deal with the problem of reaching a consensus on the annotations, a four-round Delphi method was followed by the annotators. The rhetorical patterns found by the annotators and by the algorithm are compared and their differences discussed. The algorithm reports almost all the patterns annotated by the experts and some additional patterns. The algorithm reports almost all the patterns annotated by the experts (recall: 98.11%) and some additional patterns (precision: 71.73%). These patterns correspond to rhetorical patterns within other rhetorical patterns, which were overlooked by the annotators on the basis of their contextual knowledge. These results pose issues as to how to integrate that contextual knowledge into the computational model.\n
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\n \n\n \n \n \n \n \n \n Cadential Melodies: Form-Functional Taxonomy and the Role of the Upper Voice.\n \n \n \n \n\n\n \n Hutchinson, K.; and Poon, M.\n\n\n \n\n\n\n Music Theory Online, 28(2). May 2022.\n \n\n\n\n
\n\n\n\n \n \n \"CadentialPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          hutchinson.ea2022-cadential,\n    author       = {Hutchinson, Kyle and Poon, Matthew},\n    year         = {2022},\n    title        = {Cadential {Melodies}: {Form}-{Functional} {Taxonomy} and\n                   the {Role} of the {Upper} {Voice}},\n    journal      = {Music Theory Online},\n    volume       = {28},\n    number       = {2},\n    month        = {May},\n    issn         = {1067-3040},\n    abstract     = {This article proposes that engaging with structural\n                   melodic content can expand how we conceive of cadential\n                   function and add nuance to the more harmonically driven\n                   approaches of Caplinian form-functional theory. Drawing on\n                   discussions by Schenker, Marx, and Schoenberg, we posit\n                   parallels between structural melodic configurations and\n                   the temporal formal functions of Caplinian theory. Through\n                   several analytic examples we suggest that certain melodic\n                   directions have default association with Caplin's temporal\n                   functions: ascending lines are typically associated with\n                   initiating functions, while the static prolongation of\n                   structural tones typically serves as either initiating or\n                   medial functions. Conversely, descending melodic lines,\n                   especially terminating on 1^ (authentic cadences) or 2^\n                   (half cadences) are endemic of concluding functions. We do\n                   not suggest that melodic considerations replace harmonic\n                   ones, but rather conclude that the two domains are\n                   symbiotic in the sense that melodic consideration can\n                   reinforce or undermine harmonic ones, and vice versa.\n                   Ultimately, we use this rebalancing of analytic focus as a\n                   means of reengaging with various problematic phrase types\n                   and suggest further efficacy for this approach with\n                   respect to nineteenth-century formal expansions.},\n    doi          = {10.30535/mto.28.2.4},\n    keywords     = {form-functional theory, cadences, melodic structure,\n                   phrase structure, William Caplin},\n    language     = {en},\n    tags         = {music theory},\n    url          = {https://www.mtosmt.org/issues/mto.22.28.2/mto.22.28.2.hutchinsonpoon.html}\n}\n\n
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\n This article proposes that engaging with structural melodic content can expand how we conceive of cadential function and add nuance to the more harmonically driven approaches of Caplinian form-functional theory. Drawing on discussions by Schenker, Marx, and Schoenberg, we posit parallels between structural melodic configurations and the temporal formal functions of Caplinian theory. Through several analytic examples we suggest that certain melodic directions have default association with Caplin's temporal functions: ascending lines are typically associated with initiating functions, while the static prolongation of structural tones typically serves as either initiating or medial functions. Conversely, descending melodic lines, especially terminating on 1^ (authentic cadences) or 2^ (half cadences) are endemic of concluding functions. We do not suggest that melodic considerations replace harmonic ones, but rather conclude that the two domains are symbiotic in the sense that melodic consideration can reinforce or undermine harmonic ones, and vice versa. Ultimately, we use this rebalancing of analytic focus as a means of reengaging with various problematic phrase types and suggest further efficacy for this approach with respect to nineteenth-century formal expansions.\n
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\n \n\n \n \n \n \n \n \n Computational Analysis of Musical Structures based on Morphological Filters.\n \n \n \n \n\n\n \n Lascabettes, P.; Agon, C.; Andreatta, M.; and Bloch, I.\n\n\n \n\n\n\n In MCM 2022 - 8th International Conference Mathematics and Computation in Music, Atlanta, USA, 2022. \n \n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    lascabettes.ea2022-computational,\n    author       = {Lascabettes, Paul and Agon, Carlos and Andreatta, Moreno\n                   and Bloch, Isabelle},\n    year         = {2022},\n    title        = {Computational Analysis of Musical Structures based on\n                   Morphological Filters},\n    abstract     = {This paper deals with the computational analysis of musi-\n                   cal structures by focusing on the use of morphological\n                   filters. We first propose to generalize the notion of\n                   melodic contour to a chord sequence with the chord\n                   contour, representing some formal intervallic relations\n                   between two given chords. By defining a semi-metric, we\n                   compute the self-distance matrix of a chord contour\n                   sequence. This method allows gen- erating a self-distance\n                   matrix for symbolic music representations. Self- distance\n                   matrices are used in the analysis of musical structures\n                   because blocks around the diagonal provide structural\n                   information on a musical piece. The main contribution of\n                   this paper comes from the analysis of these matrices based\n                   on mathematical morphology. Morphological filters are used\n                   to homogenize and detect regions in the self-distance\n                   matri- ces. Specifically, the opening operation has been\n                   successfully applied to reveal the blocks around the\n                   diagonal because it removes small details such as high\n                   local values and reduces all blocks around the diagonal to\n                   a zero value. Moreover, by varying the size of the\n                   morphological filter, it is possible to detect musical\n                   structures at different scales. A large opening filter\n                   identifies the main global parts of the piece, while a\n                   smaller one finds shorter musical sections. We discuss\n                   some examples that demon- strate the usefulness of this\n                   approach to detect the structures of a musical piece and\n                   its novelty within the field of symbolic music information\n                   re- search. Keywords:},\n    address      = {Atlanta, USA},\n    booktitle    = {MCM 2022 - 8th International Conference Mathematics and\n                   Computation in Music},\n    keywords     = {Chord contour,Mathematical morphology,Music\n                   structure,Self-distance matrix,Symbolic Music information\n                   research,music and mathematics},\n    mendeley-tags= {music and mathematics},\n    url          = {https://hal.archives-ouvertes.fr/hal-03641511/}\n}\n\n
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\n This paper deals with the computational analysis of musi- cal structures by focusing on the use of morphological filters. We first propose to generalize the notion of melodic contour to a chord sequence with the chord contour, representing some formal intervallic relations between two given chords. By defining a semi-metric, we compute the self-distance matrix of a chord contour sequence. This method allows gen- erating a self-distance matrix for symbolic music representations. Self- distance matrices are used in the analysis of musical structures because blocks around the diagonal provide structural information on a musical piece. The main contribution of this paper comes from the analysis of these matrices based on mathematical morphology. Morphological filters are used to homogenize and detect regions in the self-distance matri- ces. Specifically, the opening operation has been successfully applied to reveal the blocks around the diagonal because it removes small details such as high local values and reduces all blocks around the diagonal to a zero value. Moreover, by varying the size of the morphological filter, it is possible to detect musical structures at different scales. A large opening filter identifies the main global parts of the piece, while a smaller one finds shorter musical sections. We discuss some examples that demon- strate the usefulness of this approach to detect the structures of a musical piece and its novelty within the field of symbolic music information re- search. Keywords:\n
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\n \n\n \n \n \n \n \n \n A Corpus Describing Orchestral Texture in First Movements of Classical and Early-Romantic Symphonies.\n \n \n \n \n\n\n \n Le, D.; Giraud, M.; Levé, F.; and Maccarini, F.\n\n\n \n\n\n\n In 9th International Conference on Digital Libraries for Musicology, pages 27–35, Prague Czech Republic, July 2022. ACM\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    le.ea2022-corpus,\n    author       = {Le, Dinh-Viet-Toan and Giraud, Mathieu and Levé,\n                   Florence and Maccarini, Francesco},\n    year         = {2022},\n    title        = {A {Corpus} {Describing} {Orchestral} {Texture} in {First}\n                   {Movements} of {Classical} and {Early}-{Romantic}\n                   {Symphonies}},\n    address      = {Prague Czech Republic},\n    isbn         = {978-1-4503-9668-4},\n    url          = {https://dl.acm.org/doi/10.1145/3543882.3543884},\n    doi          = {10.1145/3543882.3543884},\n    abstract     = {Orchestration is the art of writing music for a possibly\n                   large ensemble of instruments, by blending or opposing\n                   their sounds and grouping them into an orchestral texture.\n                   We aim here at providing a deeper understanding of\n                   orchestration in classical and earlyromantic symphonies by\n                   analyzing, at the bar level, how the instruments of the\n                   orchestra organize into melodic, rhythmic, harmonic, and\n                   mixed layers. We formalize the description of such layers\n                   and release an open corpus with more than 7900 annotations\n                   in 24 first movements of Haydn, Mozart, and Beethoven\n                   symphonies. Initial analyses of this corpus confirm\n                   specific roles of the instruments and their families\n                   (woodwinds, brass, and strings), some evolution between\n                   composers, as well as the contribution of orchestral\n                   texture to form. The model and the corpus offer\n                   perspectives for empirical and computational studies on\n                   orchestral music.},\n    language     = {en},\n    urldate      = {2022-08-01},\n    booktitle    = {9th {International} {Conference} on {Digital} {Libraries}\n                   for {Musicology}},\n    publisher    = {ACM},\n    month        = jul,\n    keywords     = {Computational Musicology},\n    pages        = {27--35}\n}\n\n
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\n Orchestration is the art of writing music for a possibly large ensemble of instruments, by blending or opposing their sounds and grouping them into an orchestral texture. We aim here at providing a deeper understanding of orchestration in classical and earlyromantic symphonies by analyzing, at the bar level, how the instruments of the orchestra organize into melodic, rhythmic, harmonic, and mixed layers. We formalize the description of such layers and release an open corpus with more than 7900 annotations in 24 first movements of Haydn, Mozart, and Beethoven symphonies. Initial analyses of this corpus confirm specific roles of the instruments and their families (woodwinds, brass, and strings), some evolution between composers, as well as the contribution of orchestral texture to form. The model and the corpus offer perspectives for empirical and computational studies on orchestral music.\n
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\n \n\n \n \n \n \n \n \n An adaptive meta-heuristic for music plagiarism detection based on text similarity and clustering.\n \n \n \n \n\n\n \n Malandrino, D.; De Prisco, R.; Ianulardo, M.; and Zaccagnino, R.\n\n\n \n\n\n\n Data Mining and Knowledge Discovery. may 2022.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          malandrino.ea2022-adaptive,\n    author       = {Malandrino, Delfina and {De Prisco}, Roberto and\n                   Ianulardo, Mario and Zaccagnino, Rocco},\n    year         = {2022},\n    title        = {An adaptive meta-heuristic for music plagiarism detection\n                   based on text similarity and clustering},\n    abstract     = {Plagiarism is a controversial and debated topic in\n                   different fields, especially in the Music one, where the\n                   commercial market generates a huge amount of money. The\n                   lack of objective metrics to decide whether a song is a\n                   plagiarism, makes music plagiarism detection a very\n                   complex task: often decisions have to be based on\n                   subjective argumentations. Automated music analysis\n                   methods that identify music similarities can be of help.\n                   In this work, we first propose two novel such methods: a\n                   text similarity-based method and a clustering-based\n                   method. Then, we show how to combine them to get an\n                   improved (hybrid) method. The result is a novel adaptive\n                   meta-heuristic for music plagiarism detection. To assess\n                   the effectiveness of the proposed methods, considered both\n                   singularly and in the combined meta-heuristic, we\n                   performed tests on a large dataset of ascertained\n                   plagiarism and non-plagiarism cases. Results show that the\n                   meta-heuristic outperforms existing methods. Finally, we\n                   deployed the meta-heuristic into a tool , accessible as a\n                   Web application, and assessed the effectiveness,\n                   usefulness, and overall user acceptance of the tool by\n                   means of a study involving 20 people, divided into two\n                   groups, one of which with access to the tool. The study\n                   consisted in having people decide which pair of songs, in\n                   a predefined set of pairs, should be considered\n                   plagiarisms and which not. The study shows that the group\n                   supported by our tool successfully identified all\n                   plagiarism cases, performing all tasks with no errors. The\n                   whole sample agreed about the usefulness of an automatic\n                   tool that provides a measure of similarity between two\n                   songs.},\n    doi          = {10.1007/s10618-022-00835-2},\n    issn         = {1384-5810},\n    journal      = {Data Mining and Knowledge Discovery},\n    keywords     = {Clustering,Evaluation study,Multi-objective\n                   optimization,Music plagiarism detection,Text\n                   similarity,computational musicology},\n    mendeley-tags= {computational musicology},\n    month        = {may},\n    publisher    = {Springer US},\n    url          = {https://link.springer.com/10.1007/s10618-022-00835-2}\n}\n\n
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\n Plagiarism is a controversial and debated topic in different fields, especially in the Music one, where the commercial market generates a huge amount of money. The lack of objective metrics to decide whether a song is a plagiarism, makes music plagiarism detection a very complex task: often decisions have to be based on subjective argumentations. Automated music analysis methods that identify music similarities can be of help. In this work, we first propose two novel such methods: a text similarity-based method and a clustering-based method. Then, we show how to combine them to get an improved (hybrid) method. The result is a novel adaptive meta-heuristic for music plagiarism detection. To assess the effectiveness of the proposed methods, considered both singularly and in the combined meta-heuristic, we performed tests on a large dataset of ascertained plagiarism and non-plagiarism cases. Results show that the meta-heuristic outperforms existing methods. Finally, we deployed the meta-heuristic into a tool , accessible as a Web application, and assessed the effectiveness, usefulness, and overall user acceptance of the tool by means of a study involving 20 people, divided into two groups, one of which with access to the tool. The study consisted in having people decide which pair of songs, in a predefined set of pairs, should be considered plagiarisms and which not. The study shows that the group supported by our tool successfully identified all plagiarism cases, performing all tasks with no errors. The whole sample agreed about the usefulness of an automatic tool that provides a measure of similarity between two songs.\n
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\n \n\n \n \n \n \n \n A Taxonomy of Orchestral Grouping Effects Derived from Principles of Auditory Perception.\n \n \n \n\n\n \n McAdams, S.; Goodchild, M.; and Soden, K.\n\n\n \n\n\n\n Music Theory Online, 28(3): 55. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Article{          mcadams.ea2022-taxonomy,\n    author       = {McAdams, Stephen and Goodchild, Meghan and Soden, Kit},\n    year         = {2022},\n    title        = {A {Taxonomy} of {Orchestral} {Grouping} {Effects}\n                   {Derived} from {Principles} of {Auditory} {Perception}},\n    volume       = {28},\n    abstract     = {The study of timbre and orchestration in symphonic music\n                   research is underexplored, and few theories attempt to\n                   explain strategies for combining and contrasting\n                   instruments and the resulting perception of orchestral\n                   structures and textures. An analysis of orchestration\n                   treatises and musical scores reveals an implicit\n                   understanding of auditory grouping principles by which\n                   many orchestration techniques give rise to predictable\n                   perceptual effects. We present a novel theory formalized\n                   in a taxonomy of devices related to auditory grouping\n                   principles that appear frequently in Western orchestration\n                   practices from a range of historical epochs. We develop\n                   three classes of orchestration analysis categories:\n                   concurrent grouping cues result in blended combinations of\n                   instruments; sequential grouping cues result in melodic\n                   lines, the integration of surface textures, and the\n                   segregation of melodies or stratified (foreground and\n                   background) layers based on acoustic (dis)similarities;\n                   segmental grouping cues contrast sequentially presented\n                   blocks of materials and contribute to the creation of\n                   perceptual boundaries. The theory predicts\n                   orchestration-based perceptual structuring in music and\n                   may be applied to music of any style, culture, or genre.},\n    language     = {en},\n    number       = {3},\n    journal      = {Music Theory Online},\n    pages        = {55}\n}\n\n
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\n The study of timbre and orchestration in symphonic music research is underexplored, and few theories attempt to explain strategies for combining and contrasting instruments and the resulting perception of orchestral structures and textures. An analysis of orchestration treatises and musical scores reveals an implicit understanding of auditory grouping principles by which many orchestration techniques give rise to predictable perceptual effects. We present a novel theory formalized in a taxonomy of devices related to auditory grouping principles that appear frequently in Western orchestration practices from a range of historical epochs. We develop three classes of orchestration analysis categories: concurrent grouping cues result in blended combinations of instruments; sequential grouping cues result in melodic lines, the integration of surface textures, and the segregation of melodies or stratified (foreground and background) layers based on acoustic (dis)similarities; segmental grouping cues contrast sequentially presented blocks of materials and contribute to the creation of perceptual boundaries. The theory predicts orchestration-based perceptual structuring in music and may be applied to music of any style, culture, or genre.\n
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\n \n\n \n \n \n \n \n \n Statistical Methods in Music Corpus Studies: Application, UseCases, and Best Practice Examples.\n \n \n \n \n\n\n \n Müllensiefen, D.; and Frieler, K.\n\n\n \n\n\n\n In Shanahan, D.; Burgoyne, J. A.; and Quinn, I., editor(s), The Oxford Handbook of Music and Corpus Studies. Oxford University Press, 1 edition, February 2022.\n \n\n\n\n
\n\n\n\n \n \n \"StatisticalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@InCollection{     mullensiefen.ea2022-statistical,\n    author       = {M\\"{u}llensiefen, Daniel and Frieler, Klaus},\n    year         = {2022},\n    title        = {Statistical {Methods} in {Music} {Corpus} {Studies}:\n                   {Application}, {UseCases}, and {Best} {Practice}\n                   {Examples}},\n    edition      = {1},\n    isbn         = {978-0-19-094544-2 978-0-19-094547-3},\n    url          = {https://academic.oup.com/edited-volume/41992},\n    abstract     = {In this chapter, the authors explain that there are two\n                   common goals in musical corpus analysis. The rst is the\n                   description and comparison of musical corpora, the second\n                   is to establish relationships between musical structures\n                   and extra-musical data, which can refer to metadata of a\n                   particular musical piece (genre, style, and period labels,\n                   composer and performer attributions, etc.) or to\n                   listeners' perceptions and evaluations. The authors give a\n                   brief overview of basic and advanced statistical methods\n                   that have been employed in music corpus studies. The\n                   chapter covers descriptive statistics and visualizations,\n                   feature selection and aggregation using principal\n                   component analysis. In addition, random forests and linear\n                   regression methods for use in the context of corpus\n                   studies are brie y explained, as well as supervised and\n                   unsupervised classi cation techniques. Each topic and\n                   method is introduced with a conceptual explanation,\n                   suggestions for its application, and usage scenarios from\n                   the research literature.},\n    language     = {en},\n    urldate      = {2022-12-22},\n    booktitle    = {The {Oxford} {Handbook} of {Music} and {Corpus}\n                   {Studies}},\n    publisher    = {Oxford University Press},\n    editor       = {Shanahan, Daniel and Burgoyne, John Ashley and Quinn,\n                   Ian},\n    month        = feb,\n    doi          = {10.1093/oxfordhb/9780190945442.001.0001}\n}\n\n
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\n In this chapter, the authors explain that there are two common goals in musical corpus analysis. The rst is the description and comparison of musical corpora, the second is to establish relationships between musical structures and extra-musical data, which can refer to metadata of a particular musical piece (genre, style, and period labels, composer and performer attributions, etc.) or to listeners' perceptions and evaluations. The authors give a brief overview of basic and advanced statistical methods that have been employed in music corpus studies. The chapter covers descriptive statistics and visualizations, feature selection and aggregation using principal component analysis. In addition, random forests and linear regression methods for use in the context of corpus studies are brie y explained, as well as supervised and unsupervised classi cation techniques. Each topic and method is introduced with a conceptual explanation, suggestions for its application, and usage scenarios from the research literature.\n
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\n \n\n \n \n \n \n \n \n The Role of Orchestration in Shaping Musical Form: Theory and Practice of a Methodological Proposal and Its Computational Implementation.\n \n \n \n \n\n\n \n Paiva Santana, C. d.; and Guigue, D.\n\n\n \n\n\n\n Musicological Annual, 58(2): 121–153. December 2022.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          paiva-santana.ea2022-role,\n    author       = {Paiva Santana, Charles de and Guigue, Didier},\n    year         = {2022},\n    title        = {The {Role} of {Orchestration} in {Shaping} {Musical}\n                   {Form}: {Theory} and {Practice} of a {Methodological}\n                   {Proposal} and {Its} {Computational} {Implementation}},\n    volume       = {58},\n    issn         = {2350-4242, 0580-373X},\n    shorttitle   = {The {Role} of {Orchestration} in {Shaping} {Musical}\n                   {Form}},\n    url          = {https://journals.uni-lj.si/MuzikoloskiZbornik/article/view/12408},\n    doi          = {10.4312/mz.58.2.121-153},\n    abstract     = {We introduce a method for computer-assisted analysis of\n                   orchestration. We also look into the role that texture and\n                   orchestration have in structuring musical form.The method\n                   comprises a numerical representation, a hierarchy of\n                   'textural situations' and measures for heterogeneity,\n                   diversity and complexity of orchestral-textural\n                   configurations.},\n    language     = {en},\n    number       = {2},\n    urldate      = {2023-02-23},\n    journal      = {Musicological Annual},\n    month        = dec,\n    keywords     = {Computational Musicology},\n    pages        = {121--153}\n}\n\n
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\n We introduce a method for computer-assisted analysis of orchestration. We also look into the role that texture and orchestration have in structuring musical form.The method comprises a numerical representation, a hierarchy of 'textural situations' and measures for heterogeneity, diversity and complexity of orchestral-textural configurations.\n
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\n \n\n \n \n \n \n \n \n Music and Mathematics in Latin America: Major Developments in the Last 25 Years.\n \n \n \n \n\n\n \n Pareyon, G.; Almada, C.; Mathias, C.; Saraiva, C.; Moreira, D.; Carvalho, H.; Pitombeira, L.; Gentil-Nunes, P.; Mesz, B.; Amster, P.; and Riera, P.\n\n\n \n\n\n\n MusMat: Brazilian Journal of Music and Mathematics, 6(1): 12–47. June 2022.\n \n\n\n\n
\n\n\n\n \n \n \"MusicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Article{          pareyon.ea2022-music,\n    author       = {Pareyon, Gabriel and Almada, Carlos and Mathias, Carlos\n                   and Saraiva, Cecília and Moreira, Daniel and Carvalho,\n                   Hugo and Pitombeira, Liduino and Gentil-Nunes, Pauxy and\n                   Mesz, Bruno and Amster, Pablo and Riera, Pablo},\n    year         = {2022},\n    title        = {Music and {Mathematics} in {Latin} {America}: {Major}\n                   {Developments} in the {Last} 25 {Years}},\n    volume       = {6},\n    issn         = {25263757},\n    shorttitle   = {Music and {Mathematics} in {Latin} {America}},\n    url          = {https://musmat.org/wp-content/uploads/2022/06/02-Pareyon-et-al-V6N1_2022.pdf},\n    doi          = {10.46926/musmat.2022v6n1.12-47},\n    abstract     = {This text is an overview for Latin America across the\n                   field of music and musicology intersecting mathematics,\n                   including the advances from perspectives of\n                   experimentation, creation, analysis and pedagogy\n                   throughout interdisciplinary developments, particularly in\n                   the field of computational science and philosophy of\n                   science. Our main goal is to spread worldwide the richness\n                   and variety of research on music and mathematics in Latin\n                   America as well as stimulate further investigation in this\n                   fascinating intersection.},\n    language     = {en},\n    number       = {1},\n    urldate      = {2022-07-08},\n    journal      = {MusMat: Brazilian Journal of Music and Mathematics},\n    month        = jun,\n    pages        = {12--47}\n}\n\n
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\n This text is an overview for Latin America across the field of music and musicology intersecting mathematics, including the advances from perspectives of experimentation, creation, analysis and pedagogy throughout interdisciplinary developments, particularly in the field of computational science and philosophy of science. Our main goal is to spread worldwide the richness and variety of research on music and mathematics in Latin America as well as stimulate further investigation in this fascinating intersection.\n
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\n \n\n \n \n \n \n \n \n New Visual Tools for Rhythmic Partitioning Analysis of Musical Texture.\n \n \n \n \n\n\n \n Sampaio, M.; Gentil-Nunes, P.; Oliveira, V. S. d.; Oliveira, S. M. d.; and Oliveira, J. C.\n\n\n \n\n\n\n Revista Musica Theorica, 7(2): 215–246. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"NewPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          sampaio.ea2022-new,\n    author       = {{Sampaio}, {Marcos da Silva} and Gentil-Nunes, Pauxy and\n                   Oliveira, Vicente Sanches de and Oliveira, Sidnei Marques\n                   de and Oliveira, Jaderson Cardona},\n    year         = {2022},\n    title        = {New Visual Tools for Rhythmic Partitioning Analysis of\n                   Musical Texture},\n    abstract     = {The Partitional Theory of Texture provides a graphical\n                   tool, the partitiogram, to show relations between textural\n                   partitions. Despite its great utility, the partitiogram\n                   does not identify the occurrence frequency of each\n                   partition in a piece. In this paper, we propose two new\n                   partitiograms to represent partitions' occurrence\n                   frequency and to show partitions' differences among the\n                   sections of a given piece. The proposed tools made it\n                   possible to identify relevant aspects of the texture in\n                   nine works analyzed.},\n    doi          = {10.52930/mt.v7i2.240},\n    journal      = {Revista Musica Theorica},\n    keywords     = {Rhythmic Partitioning Analysis, Textural Analysis, Music\n                   Analysis, Python scripts, Music21},\n    number       = {2},\n    pages        = {215--246},\n    url          = {https://revistamusicatheorica.tema.mus.br/index.php/musica-theorica/article/view/240},\n    volume       = {7}\n}\n\n
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\n The Partitional Theory of Texture provides a graphical tool, the partitiogram, to show relations between textural partitions. Despite its great utility, the partitiogram does not identify the occurrence frequency of each partition in a piece. In this paper, we propose two new partitiograms to represent partitions' occurrence frequency and to show partitions' differences among the sections of a given piece. The proposed tools made it possible to identify relevant aspects of the texture in nine works analyzed.\n
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\n \n\n \n \n \n \n \n \n Python Scripts for Rhythmic Partitioning Analysis.\n \n \n \n \n\n\n \n Sampaio, M.; and Gentil-Nunes, P.\n\n\n \n\n\n\n MusMat - Brazilian Journal of Music and Mathematics, 6(2): 17–55. 12 2022.\n \n\n\n\n
\n\n\n\n \n \n \"PythonPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          sampaio.ea2022-python,\n    author       = {{Sampaio}, {Marcos da Silva} and Gentil-Nunes, Pauxy},\n    year         = {2022},\n    title        = {Python Scripts for Rhythmic Partitioning Analysis},\n    abstract     = {The Rhythmic Partitioning Analysis demands laborious\n                   tasks on segmentation and agglomeration/dispersion\n                   calculus. Parsemat software runs these tasks and renders\n                   indexogram and partitiogram charts. In the present paper,\n                   we introduce the Rhythmic Partitioning Scripts (RP\n                   Scripts) as an application of Rhythmic Partitioning in the\n                   Python environment. It adds some features absent in\n                   Parsemat, such as the access to measure indications of\n                   each partition, introduction of rest handling, annotation\n                   of texture info into digital scores, and other\n                   improvements. The RP Scripts collect musical events'\n                   locations and output locations and partitions' data into\n                   CSV files, render indexogram/partitiogram charts, and\n                   generate annotated MusicXML score files. RP Scripts have\n                   three components: calculator (RPC), plotter (RPP), and\n                   annotator (RPA) scripts.},\n    journal      = {MusMat - Brazilian Journal of Music and Mathematics},\n    keywords     = {Rhythmic Partitioning Analysis, Textural Analysis, Music\n                   Analysis, Python scripts, Music21},\n    month        = {12},\n    number       = {2},\n    pages        = {17--55},\n    url          = {https://musmat.org/wp-content/uploads/2022/12/02-Sampaio-Gentil-Nunes-V6N2_2022.pdf},\n    volume       = {6}\n}\n\n
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\n The Rhythmic Partitioning Analysis demands laborious tasks on segmentation and agglomeration/dispersion calculus. Parsemat software runs these tasks and renders indexogram and partitiogram charts. In the present paper, we introduce the Rhythmic Partitioning Scripts (RP Scripts) as an application of Rhythmic Partitioning in the Python environment. It adds some features absent in Parsemat, such as the access to measure indications of each partition, introduction of rest handling, annotation of texture info into digital scores, and other improvements. The RP Scripts collect musical events' locations and output locations and partitions' data into CSV files, render indexogram/partitiogram charts, and generate annotated MusicXML score files. RP Scripts have three components: calculator (RPC), plotter (RPP), and annotator (RPA) scripts.\n
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\n \n\n \n \n \n \n \n RP Scripts: Rhythmic Partitioning Scripts, Release 1.0.\n \n \n \n\n\n \n Sampaio, M.; and Gentil-Nunes, P.\n\n\n \n\n\n\n Available at ˘rlhttps://github.com/msampaio/rpScripts. Accessed on Dec. 16, 2022, 2022.\n \n\n\n\n
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@Misc{             sampaio.ea2022-rp-scripts,\n    author       = {{Sampaio}, {Marcos da Silva} and Gentil-Nunes, Pauxy},\n    year         = {2022},\n    title        = {{RP Scripts}: {Rhythmic} {Partitioning} {Scripts},\n                   Release 1.0},\n    howpublished = "Available at \\url{https://github.com/msampaio/rpScripts}.\n                   Accessed on Dec. 16, 2022"\n}\n\n
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\n \n\n \n \n \n \n \n \n Music Tools.\n \n \n \n \n\n\n \n Sampaio, M.\n\n\n \n\n\n\n 2022.\n \n\n\n\n
\n\n\n\n \n \n \"MusicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Misc{             sampaio2022-music,\n    author       = {{Sampaio}, {Marcos da Silva}},\n    year         = {2022},\n    title        = {Music Tools},\n    url          = {https://tools.sampaio.me}\n}\n\n
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\n \n\n \n \n \n \n \n \n Fuzzy Family Ties: New Methods for Measuring Familial Similarity between Contours of Variable Cardinality.\n \n \n \n \n\n\n \n Wallentinsen, K.\n\n\n \n\n\n\n Journal of Music Theory, 66(1): 93–128. April 2022.\n \n\n\n\n
\n\n\n\n \n \n \"FuzzyPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Article{          wallentinsen2022-fuzzy,\n    author       = {Wallentinsen, Kristen},\n    year         = {2022},\n    title        = {Fuzzy {Family} {Ties}: {New} {Methods} for {Measuring}\n                   {Familial} {Similarity} between {Contours} of {Variable}\n                   {Cardinality}},\n    volume       = {66},\n    issn         = {0022-2909, 1941-7497},\n    url          = {https://read.dukeupress.edu/journal-of-music-theory/article/66/1/93/313635/Fuzzy-Family-TiesNew-Methods-for-Measuring},\n    doi          = {10.1215/00222909-9534151},\n    abstract     = {Melodic contour is one of a melody's defining\n                   characteristics. Music theorists such as Michael\n                   Friedmann, Robert Morris, Elizabeth West Marvin and Paul\n                   Laprade, and Ian Quinn have developed mod els for\n                   evaluating similarities between contours, but only a few\n                   comp are similarities between pairs of contours with\n                   different lengths, and fewer still can measure shared\n                   characteristics among an entire family of contours. This\n                   article introduces a new method for evaluating familial\n                   similarities between related con tours, even if the\n                   contours have different cardinalities. The model extends\n                   theories of contour transforma tion by using fuzzy set\n                   theory and probability, measuring a contour's degree of\n                   familial membership by examining the contour's\n                   transformational pathway and calculating the probability\n                   that each move in the pathway is shared by other family\n                   members. Through the potential of differing alignments\n                   along these pathways, the model allows for the possibility\n                   that pathways may be omitted or inserted within a contour\n                   that exhibits familial resemblance, despite its different\n                   cardinality. The analytical utility of the model is then\n                   demonstrated through an analysis of melodic possibility in\n                   phased portions of Steve Reich's The Desert Music.\n                   Integrating variable cardinality into contour similarity\n                   relations in this way more adequately accounts for\n                   familial relationships between contours and can provide\n                   new and valuable insights into one of music's most\n                   fundamental elements.},\n    language     = {en},\n    number       = {1},\n    urldate      = {2022-08-21},\n    journal      = {Journal of Music Theory},\n    month        = apr,\n    tags         = {music contour},\n    pages        = {93--128}\n}\n\n
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\n Melodic contour is one of a melody's defining characteristics. Music theorists such as Michael Friedmann, Robert Morris, Elizabeth West Marvin and Paul Laprade, and Ian Quinn have developed mod els for evaluating similarities between contours, but only a few comp are similarities between pairs of contours with different lengths, and fewer still can measure shared characteristics among an entire family of contours. This article introduces a new method for evaluating familial similarities between related con tours, even if the contours have different cardinalities. The model extends theories of contour transforma tion by using fuzzy set theory and probability, measuring a contour's degree of familial membership by examining the contour's transformational pathway and calculating the probability that each move in the pathway is shared by other family members. Through the potential of differing alignments along these pathways, the model allows for the possibility that pathways may be omitted or inserted within a contour that exhibits familial resemblance, despite its different cardinality. The analytical utility of the model is then demonstrated through an analysis of melodic possibility in phased portions of Steve Reich's The Desert Music. Integrating variable cardinality into contour similarity relations in this way more adequately accounts for familial relationships between contours and can provide new and valuable insights into one of music's most fundamental elements.\n
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\n  \n 2021\n \n \n (15)\n \n \n
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\n \n\n \n \n \n \n \n Studying Structural Regularities through Abstraction Trees.\n \n \n \n\n\n \n Carnovalini, F.; Harley, N.; Homer, S.; and Rod, A.\n\n\n \n\n\n\n In Proceedings of the 15th International Symposium on CMMR, Online, Nov. 15-19, pages 165–174, 2021. \n \n\n\n\n
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@InProceedings{    carnovalini.ea2021-studying,\n    author       = {Carnovalini, Filippo and Harley, Nicholas and Homer,\n                   Steve and Rod, Antonio},\n    year         = {2021},\n    title        = {Studying Structural Regularities through Abstraction\n                   Trees},\n    booktitle    = {Proceedings of the 15th International Symposium on CMMR,\n                   Online, Nov. 15-19},\n    keywords     = {computational musicology,music\n                   representations,schenkerian analysis,structure},\n    mendeley-tags= {computational musicology},\n    pages        = {165--174}\n}\n\n
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\n \n\n \n \n \n \n \n \n Mining contour sequences for significant closed patterns.\n \n \n \n \n\n\n \n Conklin, D.\n\n\n \n\n\n\n Journal of Mathematics and Music, 0(0): 1–13. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"MiningPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          conklin2021-mining,\n    author       = {Conklin, Darrell},\n    year         = {2021},\n    title        = {Mining contour sequences for significant closed\n                   patterns},\n    abstract     = {Sequential pattern mining in music is a central part of\n                   automated music analysis and music generation. This paper\n                   evaluates sequential pattern mining on a corpus of\n                   Mozarabic chant neume sequences that have been annotated\n                   by a musicologist with intra-opus patterns. Significant\n                   patterns are discovered in three settings: all closed\n                   patterns, maximal closed patterns, and minimal closed\n                   patterns. Each setting is evaluated against the annotated\n                   patterns using the measures of recall and precision. The\n                   results indicate that it is possible to retrieve all known\n                   patterns with an acceptable precision using significant\n                   closed pattern discovery.},\n    doi          = {10.1080/17459737.2021.1903591},\n    journal      = {Journal of Mathematics and Music},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    number       = {0},\n    pages        = {1--13},\n    publisher    = {Taylor \\& Francis},\n    url          = {https://doi.org/10.1080/17459737.2021.1903591},\n    volume       = {0}\n}\n\n
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\n Sequential pattern mining in music is a central part of automated music analysis and music generation. This paper evaluates sequential pattern mining on a corpus of Mozarabic chant neume sequences that have been annotated by a musicologist with intra-opus patterns. Significant patterns are discovered in three settings: all closed patterns, maximal closed patterns, and minimal closed patterns. Each setting is evaluated against the annotated patterns using the measures of recall and precision. The results indicate that it is possible to retrieve all known patterns with an acceptable precision using significant closed pattern discovery.\n
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\n \n\n \n \n \n \n \n Cosine contours: a multipurpose representation for melodies.\n \n \n \n\n\n \n Cornelissen, B.; Zuidema, W.; and Burgoyne, J. A.\n\n\n \n\n\n\n In Proceedings of 22nd International Society for Music Information Retrieval Conference, 2021. \n \n\n\n\n
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@InProceedings{    cornelissen.ea2021-cosine,\n    author       = {Cornelissen, Bas and Zuidema, Willem and Burgoyne, John\n                   Ashley},\n    year         = {2021},\n    title        = {Cosine contours: a multipurpose representation for\n                   melodies},\n    booktitle    = {Proceedings of 22nd International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {music contour},\n    mendeley-tags= {music contour}\n}\n\n
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\n \n\n \n \n \n \n \n Statistical analysis of songs by composers of the Romantic era : A comparison of F . Schubert and his contemporaries.\n \n \n \n\n\n \n Gao, L.; Shen, H.; and Liu, C.\n\n\n \n\n\n\n Musica Hodie, 1. 2021.\n \n\n\n\n
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@Article{          gao.ea2021-statistical,\n    author       = {Gao, Linlin and Shen, He and Liu, Chang},\n    year         = {2021},\n    title        = {Statistical analysis of songs by composers of the\n                   Romantic era : A comparison of F . Schubert and his\n                   contemporaries},\n    doi          = {10.5216/mh.v21.69875},\n    journal      = {Musica Hodie},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    volume       = {1}\n}\n\n
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\n \n\n \n \n \n \n \n \n Exploring the foundations of tonality: statistical cognitive modeling of modes in the history of Western classical music.\n \n \n \n \n\n\n \n Harasim, D.; Moss, F. C.; Ramirez, M.; and Rohrmeier, M.\n\n\n \n\n\n\n Humanities and Social Sciences Communications, 8(1). 2021.\n \n\n\n\n
\n\n\n\n \n \n \"ExploringPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          harasim.ea2021-exploring,\n    author       = {Harasim, Daniel and Moss, Fabian C. and Ramirez, Matthias\n                   and Rohrmeier, Martin},\n    year         = {2021},\n    title        = {Exploring the foundations of tonality: statistical\n                   cognitive modeling of modes in the history of Western\n                   classical music},\n    abstract     = {Tonality is one of the most central theoretical concepts\n                   for the analysis of Western classical music. This study\n                   presents a novel approach for the study of its historical\n                   development, exploring in particular the concept of mode.\n                   Based on a large dataset of approximately 13,000 musical\n                   pieces in MIDI format, we present two models to infer both\n                   the number and characteristics of modes of different\n                   historical periods from first principles: a geometric\n                   model of modes as clusters of musical pieces in a\n                   non-Euclidean space, and a cognitively plausible Bayesian\n                   model of modes as Dirichlet distributions. We use the\n                   geometric model to determine the optimal number of modes\n                   for five historical epochs via unsupervised learning and\n                   apply the probabilistic model to infer the characteristics\n                   of the modes. Our results show that the inference of four\n                   modes is most plausible in the Renaissance, that two\n                   modes–corresponding to major and minor–are most\n                   appropriate in the Baroque and Classical eras, whereas no\n                   clear separation into distinct modes is found for the 19th\n                   century.},\n    doi          = {10.1057/s41599-020-00678-6},\n    issn         = {26629992},\n    journal      = {Humanities and Social Sciences Communications},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    number       = {1},\n    publisher    = {Springer US},\n    url          = {http://dx.doi.org/10.1057/s41599-020-00678-6},\n    volume       = {8}\n}\n\n
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\n Tonality is one of the most central theoretical concepts for the analysis of Western classical music. This study presents a novel approach for the study of its historical development, exploring in particular the concept of mode. Based on a large dataset of approximately 13,000 musical pieces in MIDI format, we present two models to infer both the number and characteristics of modes of different historical periods from first principles: a geometric model of modes as clusters of musical pieces in a non-Euclidean space, and a cognitively plausible Bayesian model of modes as Dirichlet distributions. We use the geometric model to determine the optimal number of modes for five historical epochs via unsupervised learning and apply the probabilistic model to infer the characteristics of the modes. Our results show that the inference of four modes is most plausible in the Renaissance, that two modes–corresponding to major and minor–are most appropriate in the Baroque and Classical eras, whereas no clear separation into distinct modes is found for the 19th century.\n
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\n \n\n \n \n \n \n \n \n The Annotated Mozart Sonatas: Score, Harmony, and Cadence.\n \n \n \n \n\n\n \n Hentschel, J.; Neuwirth, M.; and Rohrmeier, M.\n\n\n \n\n\n\n Transactions of the International Society for Music Information Retrieval, 4(1): 67–80. may 2021.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          hentschel.ea2021-annotated,\n    author       = {Hentschel, Johannes and Neuwirth, Markus and Rohrmeier,\n                   Martin},\n    year         = {2021},\n    title        = {The Annotated Mozart Sonatas: Score, Harmony, and\n                   Cadence},\n    abstract     = {This article describes a new expert-labelled dataset\n                   featuring harmonic, phrase, and cadence analyses of all\n                   piano sonatas by W.A. Mozart. The dataset draws on the\n                   DCML standard for harmonic annotation and is being\n                   published adopting the FAIR principles of Open Science.\n                   The annotations have been verified using a data\n                   triangulation procedure which is presented as an\n                   alternative approach to handling annotator subjectivity.\n                   This procedure is suited for ensuring consistency, within\n                   the dataset and beyond, despite the high level of\n                   analytical detail afforded by the employed harmonic\n                   annotation syntax. The harmony labels also encode\n                   contextual information and are therefore suited for\n                   investigating music theoretical questions related to tonal\n                   harmony and the harmonic makeup of cadences in the\n                   classical style. Apart from providing basic statistical\n                   analyses characterizing the dataset, its music theoretical\n                   potential is illustrated by two preliminary experiments,\n                   one on the terminal harmonies of cadences and the other on\n                   the relation between performance durations and harmonic\n                   density. Furthermore, particular features can be selected\n                   to produce more coarse-grained training data, for example\n                   for chord detection algorithms that require less\n                   analytical detail. Facilitating the dataset's reusability,\n                   it comes with a Python script that allows researchers to\n                   easily access various representations of the data tailored\n                   to their particular needs.},\n    doi          = {10.5334/tismir.63},\n    issn         = {2514-3298},\n    journal      = {Transactions of the International Society for Music\n                   Information Retrieval},\n    keywords     = {cadence,classical style,computational\n                   musicology,expert-annotated dataset,piano music,tonal\n                   harmony},\n    mendeley-tags= {computational musicology},\n    month        = {may},\n    number       = {1},\n    pages        = {67--80},\n    url          = {http://transactions.ismir.net/articles/10.5334/tismir.63/},\n    volume       = {4}\n}\n\n
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\n This article describes a new expert-labelled dataset featuring harmonic, phrase, and cadence analyses of all piano sonatas by W.A. Mozart. The dataset draws on the DCML standard for harmonic annotation and is being published adopting the FAIR principles of Open Science. The annotations have been verified using a data triangulation procedure which is presented as an alternative approach to handling annotator subjectivity. This procedure is suited for ensuring consistency, within the dataset and beyond, despite the high level of analytical detail afforded by the employed harmonic annotation syntax. The harmony labels also encode contextual information and are therefore suited for investigating music theoretical questions related to tonal harmony and the harmonic makeup of cadences in the classical style. Apart from providing basic statistical analyses characterizing the dataset, its music theoretical potential is illustrated by two preliminary experiments, one on the terminal harmonies of cadences and the other on the relation between performance durations and harmonic density. Furthermore, particular features can be selected to produce more coarse-grained training data, for example for chord detection algorithms that require less analytical detail. Facilitating the dataset's reusability, it comes with a Python script that allows researchers to easily access various representations of the data tailored to their particular needs.\n
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\n \n\n \n \n \n \n \n A Statistical Model for Melody Reduction.\n \n \n \n\n\n \n Hu, T.; and Arthur, C.\n\n\n \n\n\n\n In Proceedings of the Future Directions of Music Cognition International Conference, pages 1–5, 2021. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    hu.ea2021-statistical,\n    author       = {Hu, Tianxue and Arthur, Claire},\n    year         = {2021},\n    title        = {A Statistical Model for Melody Reduction},\n    booktitle    = {Proceedings of the Future Directions of Music Cognition\n                   International Conference},\n    keywords     = {music and mathematics},\n    mendeley-tags= {music and mathematics},\n    pages        = {1--5}\n}\n\n
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\n \n\n \n \n \n \n \n \n Discovering Tonal Profiles with Latent Dirichlet Allocation.\n \n \n \n \n\n\n \n Moss, F. C.; and Rohrmeier, M.\n\n\n \n\n\n\n Music & Science, 4. jan 2021.\n \n\n\n\n
\n\n\n\n \n \n \"DiscoveringPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          moss.ea2021-discovering,\n    author       = {Moss, Fabian Claude and Rohrmeier, Martin},\n    year         = {2021},\n    title        = {Discovering Tonal Profiles with Latent Dirichlet\n                   Allocation},\n    abstract     = {Music analysis, in particular harmonic analysis, is\n                   concerned with the way pitches are organized in pieces of\n                   music, and a range of empirical applications have been\n                   developed, for example, for chord recognition or key\n                   finding. Naturally, these approaches rely on some\n                   operationalization of the concepts they aim to\n                   investigate. In this study, we take a complementary\n                   approach and discover latent tonal structures in an\n                   unsupervised manner. We use the topic model Latent\n                   Dirichlet Allocation and apply it to a large historical\n                   corpus of musical pieces from the Western classical\n                   tradition. This method conceives topics as distributions\n                   of pitch classes without assuming a priori that they\n                   correspond to either chords, keys, or other harmonic\n                   phenomena. To illustrate the generative process assumed by\n                   the model, we create an artificial corpus with arbitrary\n                   parameter settings and compare the sampled pieces to real\n                   compositions. The results we obtain by applying the topic\n                   model to the musical corpus show that the inferred topics\n                   have music-theoretically meaningful interpretations. In\n                   particular, topics cover contiguous segments on the line\n                   of fifths and mostly correspond to diatonic sets.\n                   Moreover, tracing the prominence of topics over the course\n                   of music history over [Formula: see text]600 years\n                   reflects changes in the ways pitch classes are employed in\n                   musical compositions and reveals particularly strong\n                   changes at the transition from common-practice to extended\n                   tonality in the 19th century.},\n    doi          = {10.1177/20592043211048827},\n    isbn         = {2059204321},\n    issn         = {2059-2043},\n    journal      = {Music & Science},\n    keywords     = {computational musicology,corpus studies,latent dirichlet\n                   allocation,tonal pitch classes,tonality,topic modelling},\n    mendeley-tags= {computational musicology},\n    month        = {jan},\n    url          = {http://journals.sagepub.com/doi/10.1177/20592043211048827},\n    volume       = {4}\n}\n\n
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\n Music analysis, in particular harmonic analysis, is concerned with the way pitches are organized in pieces of music, and a range of empirical applications have been developed, for example, for chord recognition or key finding. Naturally, these approaches rely on some operationalization of the concepts they aim to investigate. In this study, we take a complementary approach and discover latent tonal structures in an unsupervised manner. We use the topic model Latent Dirichlet Allocation and apply it to a large historical corpus of musical pieces from the Western classical tradition. This method conceives topics as distributions of pitch classes without assuming a priori that they correspond to either chords, keys, or other harmonic phenomena. To illustrate the generative process assumed by the model, we create an artificial corpus with arbitrary parameter settings and compare the sampled pieces to real compositions. The results we obtain by applying the topic model to the musical corpus show that the inferred topics have music-theoretically meaningful interpretations. In particular, topics cover contiguous segments on the line of fifths and mostly correspond to diatonic sets. Moreover, tracing the prominence of topics over the course of music history over [Formula: see text]600 years reflects changes in the ways pitch classes are employed in musical compositions and reveals particularly strong changes at the transition from common-practice to extended tonality in the 19th century.\n
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\n \n\n \n \n \n \n \n \n End-Accented Sentences: Towards a Theory of Phrase-Rhythmic Progression.\n \n \n \n \n\n\n \n Ng, S.\n\n\n \n\n\n\n Music Theory Spectrum. jan 2021.\n \n\n\n\n
\n\n\n\n \n \n \"End-AccentedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          ng2021-end-accented,\n    author       = {Ng, Samuel},\n    year         = {2021},\n    title        = {End-Accented Sentences: Towards a Theory of\n                   Phrase-Rhythmic Progression},\n    abstract     = {For centuries, theorists have debated whether musical\n                   phrases are normatively beginning-accented or\n                   end-accented. The last two decades of the twentieth\n                   century gave beginning-accented rhythm the upper hand;\n                   yet, recent work on end-accented phrases has reinvigorated\n                   the debate. I contribute to this discussion in two ways.\n                   First, I aim to rehabilitate a central position of\n                   end-accented rhythm by drawing attention to\n                   phrase-rhythmic tendencies in classical sentence\n                   structure. My analyses show that end-accented sentential\n                   schemas are well-established compositional options in\n                   various action spaces—including Primary and Secondary\n                   Themes—in late eighteenth- and early nineteenth-century\n                   instrumental music. Moreover, integral roles of\n                   end-accented sentential themes are substantiated by their\n                   production—in tandem with their beginning-accented\n                   counterparts—of large-scale progressions analogous to\n                   tonal and formal ones. Awareness of these sentential\n                   themes re-energizes the century-old debate and deepens our\n                   understanding of phrase rhythm as a source of musical\n                   meaning. Second, in order to achieve the first goal, I\n                   develop a theory of phrase-rhythmic progression for\n                   categorizing phrase-rhythmic types and mapping their\n                   trajectories. This theory fills a gap in current spatial\n                   representations of rhythm and meter, which focus on metric\n                   dissonances and hierarchies without considerations of\n                   phrase–meter interaction.},\n    doi          = {10.1093/mts/mtaa018},\n    issn         = {0195-6167},\n    journal      = {Music Theory Spectrum},\n    keywords     = {beginning-accented phrases,end-accented\n                   phrases,narrative,phrase\n                   rhythm,representation,schema,sentence,spatial},\n    month        = {jan},\n    url          = {https://academic.oup.com/mts/advance-article/doi/10.1093/mts/mtaa018/6131575}\n}\n\n
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\n For centuries, theorists have debated whether musical phrases are normatively beginning-accented or end-accented. The last two decades of the twentieth century gave beginning-accented rhythm the upper hand; yet, recent work on end-accented phrases has reinvigorated the debate. I contribute to this discussion in two ways. First, I aim to rehabilitate a central position of end-accented rhythm by drawing attention to phrase-rhythmic tendencies in classical sentence structure. My analyses show that end-accented sentential schemas are well-established compositional options in various action spaces—including Primary and Secondary Themes—in late eighteenth- and early nineteenth-century instrumental music. Moreover, integral roles of end-accented sentential themes are substantiated by their production—in tandem with their beginning-accented counterparts—of large-scale progressions analogous to tonal and formal ones. Awareness of these sentential themes re-energizes the century-old debate and deepens our understanding of phrase rhythm as a source of musical meaning. Second, in order to achieve the first goal, I develop a theory of phrase-rhythmic progression for categorizing phrase-rhythmic types and mapping their trajectories. This theory fills a gap in current spatial representations of rhythm and meter, which focus on metric dissonances and hierarchies without considerations of phrase–meter interaction.\n
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\n \n\n \n \n \n \n \n Automatic recognition of texture in Renaissance Music.\n \n \n \n\n\n \n Parada-cabaleiro, E.; Schmitt, M.; Batliner, A.; Schuller, B.; and Schedl, M.\n\n\n \n\n\n\n In Proceedings of 22nd International Society for Music Information Retrieval Conference, pages 509–516, 2021. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    parada-cabaleiro.ea2021-automatic,\n    author       = {Parada-cabaleiro, Emilia and Schmitt, Maximilian and\n                   Batliner, Anton and Schuller, Bj{\\"{o}}rn and Schedl,\n                   Markus},\n    year         = {2021},\n    title        = {Automatic recognition of texture in Renaissance Music},\n    abstract     = {Renaissance music constitutes a resource of immense rich-\n                   ness for Western culture, as shown by its central role in\n                   digital humanities. Yet, despite the advance of computa-\n                   tional musicology in analysing other Western repertoires,\n                   the use of computer-based methods to automatically re-\n                   trieve relevant information from Renaissance music, e. g.,\n                   identifying word-painting strategies such as madrigalisms,\n                   is still underdeveloped. To this end, we propose a score-\n                   based machine learning approach for the classification of\n                   texture in Italian madrigals of the 16th century. Our out-\n                   comes indicate that Low Level Descriptors, such as inter-\n                   vals, can successfully convey differences in High Level\n                   features, such as texture. Furthermore, our baseline re-\n                   sults, particularly the ones from a Convolutional Neural\n                   Network, show that machine learning can be successfully\n                   used to automatically identify sections in madrigals asso-\n                   ciated with specific textures from symbolic sources. 1.},\n    booktitle    = {Proceedings of 22nd International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {509--516}\n}\n\n
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\n Renaissance music constitutes a resource of immense rich- ness for Western culture, as shown by its central role in digital humanities. Yet, despite the advance of computa- tional musicology in analysing other Western repertoires, the use of computer-based methods to automatically re- trieve relevant information from Renaissance music, e. g., identifying word-painting strategies such as madrigalisms, is still underdeveloped. To this end, we propose a score- based machine learning approach for the classification of texture in Italian madrigals of the 16th century. Our out- comes indicate that Low Level Descriptors, such as inter- vals, can successfully convey differences in High Level features, such as texture. Furthermore, our baseline re- sults, particularly the ones from a Convolutional Neural Network, show that machine learning can be successfully used to automatically identify sections in madrigals asso- ciated with specific textures from symbolic sources. 1.\n
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\n \n\n \n \n \n \n \n \n The Mozart Expositional Punctuation Corpus: A Dataset of Interthematic Cadences in Mozart's Sonata-Allegro Exposition.\n \n \n \n \n\n\n \n Raz, O.; Chawin, D.; and Rom, U. B.\n\n\n \n\n\n\n Empirical Musicology Review, 16(1): 134–144. dec 2021.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          raz.ea2021-mozart,\n    author       = {Raz, Omer and Chawin, Dror and Rom, Uri B.},\n    year         = {2021},\n    title        = {The Mozart Expositional Punctuation Corpus: A Dataset of\n                   Interthematic Cadences in Mozart's Sonata-Allegro\n                   Exposition},\n    abstract     = {This report documents a dataset consisting of expert\n                   annotations (symbolic data) of interthematic\n                   (higher-level) cadences in the exposition sections of all\n                   of Mozart's instrumental sonata-allegro movements.},\n    doi          = {10.18061/emr.v16i1.7648},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {cadence,classical style,computational musicology,digital\n                   musicology,expert-,musical form},\n    mendeley-tags= {computational musicology},\n    month        = {dec},\n    number       = {1},\n    pages        = {134--144},\n    url          = {https://emusicology.org/article/view/7648},\n    volume       = {16}\n}\n\n
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\n This report documents a dataset consisting of expert annotations (symbolic data) of interthematic (higher-level) cadences in the exposition sections of all of Mozart's instrumental sonata-allegro movements.\n
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\n \n\n \n \n \n \n \n \n Rhythm contour drives musical memory.\n \n \n \n \n\n\n \n Schmuckler, M. A.; and Moranis, R.\n\n\n \n\n\n\n In Future Directions of Music Cognition, December 2021. The Ohio State University Libraries\n \n\n\n\n
\n\n\n\n \n \n \"RhythmPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@InProceedings{    schmuckler.ea2021-rhythm,\n    author       = {Schmuckler, Mark A. and Moranis, Rebecca},\n    year         = {2021},\n    title        = {Rhythm contour drives musical memory},\n    url          = {https://kb.osu.edu/handle/1811/93166},\n    doi          = {10.18061/FDMC.2021.0045},\n    abstract     = {Two experiments examined listeners' use of contour\n                   information to drive memory for rhythmic patterns; these\n                   experiments were distinguished by the use of metric\n                   rhythms (Experiment 1) and ametric rhythms (Experiment 2).\n                   Both experiments employed a typical short-term memory task\n                   in which listeners heard a standard rhythm followed by a\n                   comparison rhythm. Comparison rhythms could be one of\n                   three types: an exact repetition of the standard rhythm, a\n                   same contour rhythm in which the relative durations of\n                   successive notes were comparable to the standard, and a\n                   different contour rhythm in which the relative durations\n                   of successive notes were modified relative to the\n                   standard. Analyses of d primes for same/different\n                   detection revealed that, for both studies, listeners\n                   performed better when the comparisons had different rhythm\n                   contours, relative to comparisons with the same rhythm\n                   contours. These findings converge with results\n                   investigating melodic contour, and suggest that listeners\n                   both form and use contours of novel rhythmic patterns.},\n    language     = {en},\n    urldate      = {2022-08-21},\n    booktitle    = {Future {Directions} of {Music} {Cognition}},\n    publisher    = {The Ohio State University Libraries},\n    tags         = {music contour},\n    month        = dec\n}\n\n
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\n Two experiments examined listeners' use of contour information to drive memory for rhythmic patterns; these experiments were distinguished by the use of metric rhythms (Experiment 1) and ametric rhythms (Experiment 2). Both experiments employed a typical short-term memory task in which listeners heard a standard rhythm followed by a comparison rhythm. Comparison rhythms could be one of three types: an exact repetition of the standard rhythm, a same contour rhythm in which the relative durations of successive notes were comparable to the standard, and a different contour rhythm in which the relative durations of successive notes were modified relative to the standard. Analyses of d primes for same/different detection revealed that, for both studies, listeners performed better when the comparisons had different rhythm contours, relative to comparisons with the same rhythm contours. These findings converge with results investigating melodic contour, and suggest that listeners both form and use contours of novel rhythmic patterns.\n
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\n \n\n \n \n \n \n \n Symbolic Textural Features and Melody / Accompaniment Detection in String Quartets.\n \n \n \n\n\n \n Soum-fontez, L.; and Giraud, M.\n\n\n \n\n\n\n In Proceedings of the 15th International Symposium on CMMR, Online, Nov. 15-19, 2021. \n \n\n\n\n
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@InProceedings{    soum-fontez.ea2021-symbolic,\n    author       = {Soum-fontez, Louis and Giraud, Mathieu},\n    year         = {2021},\n    title        = {Symbolic Textural Features and Melody / Accompaniment\n                   Detection in String Quartets},\n    booktitle    = {Proceedings of the 15th International Symposium on CMMR,\n                   Online, Nov. 15-19},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology}\n}\n\n
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\n \n\n \n \n \n \n \n Measuring the Amount of Freedom for Compositional Choices in a Textural Perspective Daniel Moreira de Sousa.\n \n \n \n\n\n \n de Sousa, D. M.\n\n\n \n\n\n\n MusMat: Brazilian Journal of Music and Mathematics, V(1): 126–156. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@Article{          sousa2021-measuring,\n    author       = {de Sousa, Daniel Moreira},\n    year         = {2021},\n    title        = {Measuring the Amount of Freedom for Compositional Choices\n                   in a Textural Perspective Daniel Moreira de Sousa},\n    abstract     = {In this paper I discuss the relation between the number\n                   of available compositional choices and the complexity in\n                   dealing with them in the scope of musical texture. First,\n                   I discuss the paradigm of compositional choice in light of\n                   the number of variables for a given situation. Then, I\n                   introduce the concept of compositional entropy-–a\n                   proposal for measuring the amount of freedom that is\n                   implied in each compositional choice when selecting a\n                   given musical object. This computation depends on the\n                   number of available variables provided by the chosen\n                   musical object so that the higher the compositional\n                   entropy, the more complex is the choosing process as it\n                   provides a high number of possibilities to be chosen. This\n                   formulation enables the discussion of compositional\n                   choices in a view of probability and combinatorial\n                   permutations. In the second part of the article, I apply\n                   this concept in the textural domain. To do so, I introduce\n                   a series of concepts and formulations regarding musical\n                   texture to enable such a discussion. Finally, I\n                   demonstrate how to measure the compositional entropy of\n                   textures, considering both the number of possible textural\n                   configurations a composer may manage for a given number of\n                   sound- ing components (exhaustive taxonomy of textures)\n                   and how many different ways a given configuration can be\n                   realized as music in the score, considering only textural\n                   terms (exhaustive taxonomy of realizations).},\n    doi          = {10.46926/musmat.2021v5n1.126-156},\n    journal      = {MusMat: Brazilian Journal of Music and Mathematics},\n    keywords     = {Compositional entropy. Musical texture. Textural l,music\n                   texture},\n    mendeley-tags= {music texture},\n    number       = {1},\n    pages        = {126--156},\n    volume       = {V}\n}\n\n
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\n In this paper I discuss the relation between the number of available compositional choices and the complexity in dealing with them in the scope of musical texture. First, I discuss the paradigm of compositional choice in light of the number of variables for a given situation. Then, I introduce the concept of compositional entropy-–a proposal for measuring the amount of freedom that is implied in each compositional choice when selecting a given musical object. This computation depends on the number of available variables provided by the chosen musical object so that the higher the compositional entropy, the more complex is the choosing process as it provides a high number of possibilities to be chosen. This formulation enables the discussion of compositional choices in a view of probability and combinatorial permutations. In the second part of the article, I apply this concept in the textural domain. To do so, I introduce a series of concepts and formulations regarding musical texture to enable such a discussion. Finally, I demonstrate how to measure the compositional entropy of textures, considering both the number of possible textural configurations a composer may manage for a given number of sound- ing components (exhaustive taxonomy of textures) and how many different ways a given configuration can be realized as music in the score, considering only textural terms (exhaustive taxonomy of realizations).\n
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\n \n\n \n \n \n \n \n An evaluation of musical pattern discovery algorithms using a visualisation application.\n \n \n \n\n\n \n Wargelin, M.\n\n\n \n\n\n\n Ph.D. Thesis, University of Helsinki, 2021.\n \n\n\n\n
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@PhDThesis{        wargelin2021-evaluation,\n    author       = {Wargelin, Matias},\n    year         = {2021},\n    title        = {An evaluation of musical pattern discovery algorithms\n                   using a visualisation application},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    school       = {University of Helsinki},\n    type         = {Master's Thesis}\n}\n\n
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\n  \n 2020\n \n \n (28)\n \n \n
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\n \n\n \n \n \n \n \n \n Implementação de um sistema composicional semiaberto a partir da similaridade entre conjuntos de classes de notas.\n \n \n \n \n\n\n \n Braga, V.; Penchel, J.; Chagas, I.; Furman, R.; Proença, P.; and Pitombeira, L.\n\n\n \n\n\n\n OPUS, 26(2): 1. oct 2020.\n \n\n\n\n
\n\n\n\n \n \n \"ImplementaçãoPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          braga.ea2020-implementacao,\n    author       = {Braga, Vinicius and Penchel, Jo{\\~{a}}o and Chagas, Igor\n                   and Furman, Rodrigo and Proen{\\c{c}}a, Pedro and\n                   Pitombeira, Liduino},\n    year         = {2020},\n    title        = {Implementa{\\c{c}}{\\~{a}}o de um sistema composicional\n                   semiaberto a partir da similaridade entre conjuntos de\n                   classes de notas},\n    abstract     = {Este trabalho descreve a formaliza{\\c{c}}{\\~{a}}o e\n                   aplica{\\c{c}}{\\~{a}}o de um sistema composicional,\n                   denominado Similare, que articula micro e macroestrutura\n                   tomando como base as rela{\\c{c}}{\\~{o}}es de similaridade\n                   entre conjuntos de classes de notas. Ap{\\'{o}}s o exame\n                   detalhado dos dois referenciais que d{\\~{a}}o\n                   sustenta{\\c{c}}{\\~{a}}o te{\\'{o}}rica ao trabalho\n                   (sistemas composicionais e similaridade), o sistema foi\n                   definido e, a partir dele, duas obras foram planejadas:\n                   uma para quarteto de cordas e outra para piano solo.\n                   Durante o processo de pesquisa, aplicativos em Python\n                   foram elaborados para auxiliar os compositores na\n                   manipula{\\c{c}}{\\~{a}}o dos conjuntos.},\n    doi          = {10.20504/opus2020b2611},\n    issn         = {15177017},\n    journal      = {OPUS},\n    keywords     = {Implementation,Sistemas Composicionais. Planejamento\n                   Composiciona,music similarity},\n    mendeley-tags= {music similarity},\n    month        = {oct},\n    number       = {2},\n    pages        = {1},\n    url          = {https://www.anppom.com.br/revista/index.php/opus/article/view/opus2020b2611},\n    volume       = {26}\n}\n\n
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\n Este trabalho descreve a formalização e aplicação de um sistema composicional, denominado Similare, que articula micro e macroestrutura tomando como base as relações de similaridade entre conjuntos de classes de notas. Após o exame detalhado dos dois referenciais que dão sustentação teórica ao trabalho (sistemas composicionais e similaridade), o sistema foi definido e, a partir dele, duas obras foram planejadas: uma para quarteto de cordas e outra para piano solo. Durante o processo de pesquisa, aplicativos em Python foram elaborados para auxiliar os compositores na manipulação dos conjuntos.\n
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\n \n\n \n \n \n \n \n \n Digital Approaches to Troubadour Song.\n \n \n \n \n\n\n \n Chapman, K. E.\n\n\n \n\n\n\n Ph.D. Thesis, Indiana University, 2020.\n \n\n\n\n
\n\n\n\n \n \n \"DigitalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@PhDThesis{        chapman2020-digital,\n    author       = {Chapman, Katie Elizabeth},\n    year         = {2020},\n    title        = {Digital Approaches to Troubadour Song},\n    abstract     = {The troubadours were poet-composers who flourished in\n                   Occitania (today southern France) and surrounding areas\n                   during the twelfth and thirteenth centuries. Their lyric\n                   poems survive in chansonniers (songbooks) which usually\n                   contain only the texts. A fraction of the melodies that\n                   accompanied these poems were written down; fewer than 350\n                   melodies survive for a lyric corpus of over 2,600 songs\n                   which appear over 13,000 times in all extant sources. This\n                   dissertation is part of a larger project whose aim is\n                   twofold: to create an openaccess, electronic, searchable\n                   archive of these melodies and to apply computational\n                   methods of analysis to identify the musical\n                   characteristics of the melodies, find patterns and\n                   relationships, and track trends in style both over time\n                   and within the works of individual authors. In this study,\n                   I first illustrate the methodology I followed to assess\n                   and encode the corpus of troubadour melodies and give an\n                   overview of the types of tools used to analyze the encoded\n                   melodies. In the subsequent chapters, I present five case\n                   studies which investigate musical features of the\n                   repertory through computational and statistical\n                   approaches, where I confirm, revise, or expand on existing\n                   knowledge of the repertory. The first case study\n                   identifies the extent and features of Guiraut Riquier's\n                   melismatic writing by applying analytical techniques\n                   typically used to analyze textual corpora. The second case\n                   study applies a different technique borrowed from\n                   computational linguistics, Latent Semantic Analysis (LSA),\n                   to track the similarity of melodies with versions extant\n                   in multiple sources and to compare the phrases of melodies\n                   in one manuscript which have notation for more than one\n                   stanza. The three case studies in Chapter III adopt other\n                   analytical approaches to investigate and compare the pitch\n                   and interval content of the melodies. These studies help\n                   identify patterns in pitch organization in the entire\n                   repertory, point out stylistic trends of specific\n                   troubadours, and compare selected musical features by\n                   source. Overall, this study demonstrates the possibilities\n                   of computational approaches to contribute to existing\n                   scholarship on this repertory. Furthermore, the digital\n                   archive created for this project aims to empower\n                   additional research on the music of the troubadours,\n                   including the study of corpus-wide characteristics, the\n                   analysis of stylistic traits in specific authors or\n                   sources, and changes in style over the course of the\n                   tradition.},\n    keywords     = {computational musicology,digital\n                   musicology,musicology,troubadours},\n    mendeley-tags= {musicology},\n    school       = {Indiana University},\n    type         = {Ph.D. Dissertation},\n    url          = {https://scholarworks.iu.edu/dspace/handle/2022/25114}\n}\n\n
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\n The troubadours were poet-composers who flourished in Occitania (today southern France) and surrounding areas during the twelfth and thirteenth centuries. Their lyric poems survive in chansonniers (songbooks) which usually contain only the texts. A fraction of the melodies that accompanied these poems were written down; fewer than 350 melodies survive for a lyric corpus of over 2,600 songs which appear over 13,000 times in all extant sources. This dissertation is part of a larger project whose aim is twofold: to create an openaccess, electronic, searchable archive of these melodies and to apply computational methods of analysis to identify the musical characteristics of the melodies, find patterns and relationships, and track trends in style both over time and within the works of individual authors. In this study, I first illustrate the methodology I followed to assess and encode the corpus of troubadour melodies and give an overview of the types of tools used to analyze the encoded melodies. In the subsequent chapters, I present five case studies which investigate musical features of the repertory through computational and statistical approaches, where I confirm, revise, or expand on existing knowledge of the repertory. The first case study identifies the extent and features of Guiraut Riquier's melismatic writing by applying analytical techniques typically used to analyze textual corpora. The second case study applies a different technique borrowed from computational linguistics, Latent Semantic Analysis (LSA), to track the similarity of melodies with versions extant in multiple sources and to compare the phrases of melodies in one manuscript which have notation for more than one stanza. The three case studies in Chapter III adopt other analytical approaches to investigate and compare the pitch and interval content of the melodies. These studies help identify patterns in pitch organization in the entire repertory, point out stylistic trends of specific troubadours, and compare selected musical features by source. Overall, this study demonstrates the possibilities of computational approaches to contribute to existing scholarship on this repertory. Furthermore, the digital archive created for this project aims to empower additional research on the music of the troubadours, including the study of corpus-wide characteristics, the analysis of stylistic traits in specific authors or sources, and changes in style over the course of the tradition.\n
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\n \n\n \n \n \n \n \n \n Mode classification and natural units in plainchant.\n \n \n \n \n\n\n \n Cornelissen, B.; Zuidema, W.; and Burgoyne, J. A.\n\n\n \n\n\n\n In Proceedings of 21th International Society for Music Information Retrieval Conference, Montréal, Canada, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"ModePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    cornelissen.ea2020-mode,\n    author       = {Cornelissen, Bas and Zuidema, Willen and Burgoyne, John\n                   Ashley},\n    year         = {2020},\n    title        = {Mode classification and natural units in plainchant},\n    address      = {Montr{\\'{e}}al, Canada},\n    booktitle    = {Proceedings of 21th International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    url          = {https://program.ismir2020.org/poster_232.html}\n}\n\n
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\n \n\n \n \n \n \n \n \n Studying Large Plainchant Corpora Using chant21.\n \n \n \n \n\n\n \n Cornelissen, B.; Zuidema, W.; and Burgoyne, J. A.\n\n\n \n\n\n\n In Proceedings of 7th International Conference on Digital Libraries for Musicology, Montréal, Canada, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"StudyingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    cornelissen.ea2020-studying,\n    author       = {Cornelissen, Bas and Zuidema, Willem and Burgoyne, John\n                   Ashley},\n    year         = {2020},\n    title        = {Studying Large Plainchant Corpora Using chant21},\n    address      = {Montr{\\'{e}}al, Canada},\n    booktitle    = {Proceedings of 7th International Conference on Digital\n                   Libraries for Musicology},\n    keywords     = {2020,acm reference format,and john ashley burgoyne,bas\n                   cornelissen,computational\n                   musicology,datasets,differentia,gabc,melodic\n                   arch,plainchant,study-,volpiano,willem zuidema},\n    mendeley-tags= {computational musicology},\n    url          = {https://dlfm.web.ox.ac.uk/}\n}\n\n
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\n \n\n \n \n \n \n \n \n Quelques propos sur les outils et les méthodes audionumériques en musicologie. L'interdisciplinarité comme rupture épistémologique.\n \n \n \n \n\n\n \n Couprie, P.\n\n\n \n\n\n\n Revue musicale OICRM, 6(2): 25–44. March 2020.\n \n\n\n\n
\n\n\n\n \n \n \"QuelquesPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          couprie2020-quelques,\n    author       = {Couprie, Pierre},\n    year         = {2020},\n    title        = {Quelques propos sur les outils et les méthodes\n                   audionumériques en musicologie. {L}'interdisciplinarité\n                   comme rupture épistémologique},\n    volume       = {6},\n    issn         = {2368-7061},\n    url          = {http://id.erudit.org/iderudit/ 1068384ar},\n    doi          = {10.7202/1068384ar},\n    abstract     = {From the first uses of databases in the 1970s to recent\n                   research on the analysis of audio files, musicologists\n                   have progressively integrated digital technologies into\n                   their working methods. However, while some software such\n                   as iAnalyse offers interfaces adapted to the human\n                   sciences, it has been observed that these technologies are\n                   still difficult to manipulate without a solid knowledge of\n                   computer science or acoustics. In this article, the author\n                   presents an interdisciplinary practice of research at the\n                   heart of digital musicology that covers a very wide field\n                   of activities ranging from the use of software to improve\n                   existing methods to the development of new methods that\n                   are necessary to study specific corpus. In this case, the\n                   deep transformation of the nature of musicological\n                   practice itself, the move towards a hybrid discipline and\n                   the change of perspective on a complex musical object\n                   highlight a real epistemological rupture.},\n    language     = {fr},\n    number       = {2},\n    urldate      = {2023-04-12},\n    journal      = {Revue musicale OICRM},\n    month        = mar,\n    pages        = {25--44}\n}\n\n
\n
\n\n\n
\n From the first uses of databases in the 1970s to recent research on the analysis of audio files, musicologists have progressively integrated digital technologies into their working methods. However, while some software such as iAnalyse offers interfaces adapted to the human sciences, it has been observed that these technologies are still difficult to manipulate without a solid knowledge of computer science or acoustics. In this article, the author presents an interdisciplinary practice of research at the heart of digital musicology that covers a very wide field of activities ranging from the use of software to improve existing methods to the development of new methods that are necessary to study specific corpus. In this case, the deep transformation of the nature of musicological practice itself, the move towards a hybrid discipline and the change of perspective on a complex musical object highlight a real epistemological rupture.\n
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\n \n\n \n \n \n \n \n \n Using Note-Level Music Encodings to Facilitate Interdisciplinary Research on Human Engagement with Music.\n \n \n \n \n\n\n \n Devaney, J.\n\n\n \n\n\n\n Transactions of the International Society for Music Information Retrieval, 3(1): 205–217. oct 2020.\n \n\n\n\n
\n\n\n\n \n \n \"UsingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          devaney2020-using,\n    author       = {Devaney, Johanna},\n    year         = {2020},\n    title        = {Using Note-Level Music Encodings to Facilitate\n                   Interdisciplinary Research on Human Engagement with\n                   Music},\n    abstract     = {Music encoding can link disparate types of musical data\n                   for the purposes of archiving and search. The encoding of\n                   human response data explicitly in relation to musical\n                   notes facilitates the study of the ways humans engage with\n                   music as performers and listeners. This paper reflects on\n                   the developments and trends in formal music encoding\n                   systems as well as the types of data representations used\n                   in corpora released by researchers working on expert music\n                   analyses, musical performances, and listener responses. It\n                   argues that while the specificity (and often simplicity)\n                   afforded by project-specific encoding formats may be\n                   useful for individual research projects, larger-scale\n                   interdisciplinary research would be better served by\n                   explicit, formalized linking of data to specific musical\n                   elements. The paper concludes by offering some concrete\n                   suggestions for how to achieve this goal.},\n    doi          = {10.5334/tismir.56},\n    issn         = {2514-3298},\n    journal      = {Transactions of the International Society for Music\n                   Information Retrieval},\n    keywords     = {computational musicology,listener,music analysis,music\n                   encoding,music performance,musical elements,musical\n                   notes},\n    mendeley-tags= {computational musicology},\n    month        = {oct},\n    number       = {1},\n    pages        = {205--217},\n    url          = {http://transactions.ismir.net/articles/10.5334/tismir.56/},\n    volume       = {3}\n}\n\n
\n
\n\n\n
\n Music encoding can link disparate types of musical data for the purposes of archiving and search. The encoding of human response data explicitly in relation to musical notes facilitates the study of the ways humans engage with music as performers and listeners. This paper reflects on the developments and trends in formal music encoding systems as well as the types of data representations used in corpora released by researchers working on expert music analyses, musical performances, and listener responses. It argues that while the specificity (and often simplicity) afforded by project-specific encoding formats may be useful for individual research projects, larger-scale interdisciplinary research would be better served by explicit, formalized linking of data to specific musical elements. The paper concludes by offering some concrete suggestions for how to achieve this goal.\n
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\n \n\n \n \n \n \n \n Voice-Leading Schema Recognition Using Rhythm and Pitch Features.\n \n \n \n\n\n \n Finkensiep, C.; Déguernel, K.; Neuwirth, M.; and Rohrmeier, M.\n\n\n \n\n\n\n In Proceedings of 21st International Conference on Music Information Retrieval, pages 520–526, Montréal, Canada, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    finkensiep.ea2020-voice-leading,\n    author       = {Finkensiep, Christoph and D{\\'{e}}guernel, Ken and\n                   Neuwirth, Markus and Rohrmeier, Martin},\n    year         = {2020},\n    title        = {Voice-Leading Schema Recognition Using Rhythm and Pitch\n                   Features},\n    address      = {Montr{\\'{e}}al, Canada},\n    booktitle    = {Proceedings of 21st International Conference on Music\n                   Information Retrieval},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    pages        = {520--526}\n}\n\n
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\n \n\n \n \n \n \n \n \n Miles Vs. Trane: Computational and Statistical Comparison of the Improvisatory Styles of Miles Davis and John Coltrane.\n \n \n \n \n\n\n \n Frieler, K.\n\n\n \n\n\n\n Jazz Perspectives, 12(1): 123–145. jan 2020.\n \n\n\n\n
\n\n\n\n \n \n \"MilesPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          frieler2020-miles,\n    author       = {Frieler, Klaus},\n    year         = {2020},\n    title        = {Miles Vs. Trane: Computational and Statistical Comparison\n                   of the Improvisatory Styles of Miles Davis and John\n                   Coltrane},\n    abstract     = {Much has been written about John Coltrane and Miles\n                   Davis, from autobiographical works to detailed\n                   musicological analyses and cultural/sociological accounts\n                   of their lives, work, and legacy. Fewer publications are\n                   concerned with a direct comparison of both artists'\n                   approach to improvisation. I introduce a new analytical\n                   perspective, developed in the context of the Jazzomat\n                   Research Project, by using computational and statistical\n                   methods. Based on a large set of solo transcriptions taken\n                   from the Weimar Jazz Database spanning different stylistic\n                   phases for both artists (20 solos by Coltrane and 19 solos\n                   by Davis), I identify common and differing stylistic\n                   traits. This approach utilizes a set of 143 musical\n                   features extracted from the solos. Results indicate that\n                   both players differ in quite many aspects. Clich{\\'{e}}s\n                   of the “extroverted” style of Coltrane and the\n                   “introverted” style of Davis are evidenced by vastly\n                   different note densities and overall spacing of phrases.\n                   Some surprising and subtle differences also showed up. For\n                   instance, Davis has a tendency to avoid the third of the\n                   underlying chord and also major and minor third intervals,\n                   whereas Coltrane has a preference for playing out chords.\n                   Furthermore, both players seem to have no large overlap in\n                   their respective pattern vocabularies.},\n    doi          = {10.1080/17494060.2020.1734053},\n    issn         = {1749-4060},\n    journal      = {Jazz Perspectives},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    month        = {jan},\n    number       = {1},\n    pages        = {123--145},\n    publisher    = {Taylor \\& Francis},\n    url          = {https://www.tandfonline.com/doi/full/10.1080/17494060.2020.1734053},\n    volume       = {12}\n}\n\n
\n
\n\n\n
\n Much has been written about John Coltrane and Miles Davis, from autobiographical works to detailed musicological analyses and cultural/sociological accounts of their lives, work, and legacy. Fewer publications are concerned with a direct comparison of both artists' approach to improvisation. I introduce a new analytical perspective, developed in the context of the Jazzomat Research Project, by using computational and statistical methods. Based on a large set of solo transcriptions taken from the Weimar Jazz Database spanning different stylistic phases for both artists (20 solos by Coltrane and 19 solos by Davis), I identify common and differing stylistic traits. This approach utilizes a set of 143 musical features extracted from the solos. Results indicate that both players differ in quite many aspects. Clichés of the “extroverted” style of Coltrane and the “introverted” style of Davis are evidenced by vastly different note densities and overall spacing of phrases. Some surprising and subtle differences also showed up. For instance, Davis has a tendency to avoid the third of the underlying chord and also major and minor third intervals, whereas Coltrane has a preference for playing out chords. Furthermore, both players seem to have no large overlap in their respective pattern vocabularies.\n
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\n \n\n \n \n \n \n \n Glossário de termos schenkerianos.\n \n \n \n\n\n \n Gerling, C. C.; and de Barros, G. S.\n\n\n \n\n\n\n TeMA, Salvador, BA, 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             gerling.ea2020-glossario,\n    author       = {Gerling, Cristina Capparelli and de Barros, Guilherme\n                   Sauerbronn},\n    year         = {2020},\n    title        = {Gloss{\\'{a}}rio de termos schenkerianos},\n    address      = {Salvador, BA},\n    isbn         = {9786599193903},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {TeMA}\n}\n\n
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\n \n\n \n \n \n \n \n \n Reprise Structures in Haydn's Op. 50 Minuets.\n \n \n \n \n\n\n \n Inman, S. M.\n\n\n \n\n\n\n Indiana Theory Review, 36(1-2): 23–55. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"ReprisePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          inman2020-reprise,\n    author       = {Inman, Samantha M.},\n    year         = {2020},\n    title        = {Reprise Structures in Haydn's Op. 50 Minuets},\n    issn         = {02718022, 24747777},\n    journal      = {Indiana Theory Review},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1-2},\n    pages        = {23--55},\n    publisher    = {Department of Music Theory, Jacobs School of Music,\n                   Indiana University, Indiana University Press, Trustees of\n                   Indiana University},\n    url          = {https://www.jstor.org/stable/10.2979/inditheorevi.36.1-2.02},\n    volume       = {36}\n}\n\n
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\n \n\n \n \n \n \n \n Music genre descriptor for classification based on tonnetz trajectories.\n \n \n \n\n\n \n Karystinaios, E.; Guichaoua, C.; Andreatta, M.; Bigo, L.; and Bloch, I.\n\n\n \n\n\n\n Journées d'Informatique Musicale. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          karystinaios.ea2020-music,\n    author       = {Karystinaios, Emmanouil and Guichaoua, Corentin and\n                   Andreatta, Moreno and Bigo, Louis and Bloch, Isabelle},\n    year         = {2020},\n    title        = {Music genre descriptor for classification based on\n                   tonnetz trajectories},\n    journal      = {Journ{\\'{e}}es d'Informatique Musicale},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval}\n}\n\n
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\n \n\n \n \n \n \n \n A Survey on Visualizations for Musical Data.\n \n \n \n\n\n \n Khulusi, R.; Kusnick, J.; Meinecke, C.; Gillmann, C.; Focht, J.; and Jänicke, S.\n\n\n \n\n\n\n Computer Graphics Forum, 00(00): 1–28. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          khulusi.ea2020-survey,\n    author       = {Khulusi, R. and Kusnick, J. and Meinecke, C. and\n                   Gillmann, C. and Focht, J. and J{\\"{a}}nicke, S.},\n    year         = {2020},\n    title        = {A Survey on Visualizations for Musical Data},\n    abstract     = {Digital methods are increasingly applied to store,\n                   structure and analyse vast amounts of musical data. In\n                   this context, visualization plays a crucial role, as it\n                   assists musicologists and non-expert users in data\n                   analysis and in gaining new knowledge. This survey focuses\n                   on this unique link between musicology and visualization.\n                   We classify 129 related works according to the visualized\n                   data types, and we analyse which visualization techniques\n                   were applied for certain research inquiries and to fulfill\n                   specific tasks. Next to scientific references, we take\n                   commercial music software and public websites into\n                   account, that contribute novel concepts of visualizing\n                   musicological data. We encounter different aspects of\n                   uncertainty as major problems when dealing with\n                   musicological data and show how occurring inconsistencies\n                   are processed and visually communicated. Drawing from our\n                   overview in the field, we identify open challenges for\n                   research on the interface of musicology and visualization\n                   to be tackled in the future.},\n    doi          = {10.1111/cgf.13905},\n    issn         = {14678659},\n    journal      = {Computer Graphics Forum},\n    keywords     = {computational musicology,information\n                   visualization,visualization},\n    mendeley-tags= {computational musicology},\n    number       = {00},\n    pages        = {1--28},\n    volume       = {00}\n}\n\n
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\n Digital methods are increasingly applied to store, structure and analyse vast amounts of musical data. In this context, visualization plays a crucial role, as it assists musicologists and non-expert users in data analysis and in gaining new knowledge. This survey focuses on this unique link between musicology and visualization. We classify 129 related works according to the visualized data types, and we analyse which visualization techniques were applied for certain research inquiries and to fulfill specific tasks. Next to scientific references, we take commercial music software and public websites into account, that contribute novel concepts of visualizing musicological data. We encounter different aspects of uncertainty as major problems when dealing with musicological data and show how occurring inconsistencies are processed and visually communicated. Drawing from our overview in the field, we identify open challenges for research on the interface of musicology and visualization to be tackled in the future.\n
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\n \n\n \n \n \n \n \n A corpus-based analysis of syncopated patterns in Ragtime.\n \n \n \n\n\n \n Kirlin, P. B\n\n\n \n\n\n\n In Proceedings of 21th International Society for Music Information Retrieval Conference, Montréal, Canada, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    kirlin2020-corpus-based,\n    author       = {Kirlin, Phillip B},\n    year         = {2020},\n    title        = {A corpus-based analysis of syncopated patterns in\n                   Ragtime},\n    address      = {Montr{\\'{e}}al, Canada},\n    booktitle    = {Proceedings of 21th International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval}\n}\n\n
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\n \n\n \n \n \n \n \n Rule mining for local boundary detection in melodies.\n \n \n \n\n\n \n van Kranenburg, P.\n\n\n \n\n\n\n In Proceedings of 21st International Conference on Music Information Retrieval, pages 271–278, Montréal, Canada, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    kranenburg2020-rule,\n    author       = {van Kranenburg, Peter},\n    year         = {2020},\n    title        = {Rule mining for local boundary detection in melodies},\n    address      = {Montr{\\'{e}}al, Canada},\n    booktitle    = {Proceedings of 21st International Conference on Music\n                   Information Retrieval},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {271--278}\n}\n\n
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\n \n\n \n \n \n \n \n Historiography of the form of symbolic music through a computer-assisted analysis.\n \n \n \n\n\n \n Kutschke, B. R.; and Bachmann, T.\n\n\n \n\n\n\n In Proceedings of the 17th Sound and Music Computing Conference, pages 386–393, Torino, 2020. \n \n\n\n\n
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@InProceedings{    kutschke.ea2020-historiography,\n    author       = {Kutschke, Beate Ruth and Bachmann, Tobias},\n    year         = {2020},\n    title        = {Historiography of the form of symbolic music through a\n                   computer-assisted analysis},\n    address      = {Torino},\n    booktitle    = {Proceedings of the 17th Sound and Music Computing\n                   Conference},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval},\n    pages        = {386--393}\n}\n\n
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\n \n\n \n \n \n \n \n \n Grouping compositions based on similarity of music themes.\n \n \n \n \n\n\n \n Laskowska, B.; and Kamola, M.\n\n\n \n\n\n\n PLoS ONE, 15(10). oct 2020.\n \n\n\n\n
\n\n\n\n \n \n \"GroupingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          laskowska.ea2020-grouping,\n    author       = {Laskowska, Barbara and Kamola, Mariusz},\n    year         = {2020},\n    title        = {Grouping compositions based on similarity of music\n                   themes},\n    doi          = {10.1371/journal.pone.0240443},\n    editor       = {Amancio, Diego Raphael},\n    isbn         = {1111111111},\n    issn         = {1932-6203},\n    journal      = {PLoS ONE},\n    keywords     = {music similarity},\n    mendeley-tags= {music similarity},\n    month        = {oct},\n    number       = {10},\n    url          = {http://dx.doi.org/10.1371/journal.pone.0240443\n                   https://dx.plos.org/10.1371/journal.pone.0240443},\n    volume       = {15}\n}\n\n
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\n \n\n \n \n \n \n \n \n The Tonal Diffusion Model.\n \n \n \n \n\n\n \n Lieck, R.; Moss, F. C.; and Rohrmeier, M.\n\n\n \n\n\n\n , 3: 153–164. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          lieck.ea2020-tonal,\n    author       = {Lieck, Robert and Moss, Fabian Claude and Rohrmeier,\n                   Martin},\n    year         = {2020},\n    title        = {The Tonal Diffusion Model},\n    keywords     = {bayesian generative model,cognitive modeling,music\n                   theory,pitch-class distributions,tonality,tonnetz},\n    mendeley-tags= {music theory},\n    pages        = {153--164},\n    url          = {https://transactions.ismir.net/articles/10.5334/tismir.46/},\n    volume       = {3}\n}\n\n
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\n \n\n \n \n \n \n \n \n Joseph Haydn and the New Formenlehre: Teaching Sonata Form with His Solo Keyboard Works.\n \n \n \n \n\n\n \n MacKay, J. S.\n\n\n \n\n\n\n HAYDN: Online Journal of the Haydn Society of North America, 10(2). 2020.\n \n\n\n\n
\n\n\n\n \n \n \"JosephPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Article{          mackay2020-joseph,\n    author       = {MacKay, James S.},\n    year         = {2020},\n    title        = {Joseph {Haydn} and the {New} {Formenlehre}: {Teaching}\n                   {Sonata} {Form} with {His} {Solo} {Keyboard} {Works}},\n    volume       = {10},\n    url          = {https://remix.berklee.edu/haydn-journal/vol10/iss2/4},\n    number       = {2},\n    tags         = {music analysis},\n    journal      = {HAYDN: Online Journal of the Haydn Society of North\n                   America}\n}\n\n
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\n \n\n \n \n \n \n \n Not All Roads Lead to Rome: Pitch Representation and Model Architecture for Automatic Harmonic Analysis.\n \n \n \n\n\n \n Micchi, G.; Gotham, M.; and Giraud, M.\n\n\n \n\n\n\n Transactions of the International Society for Music Information Retrieval, 3(1): 42–54. 2020.\n \n\n\n\n
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@Article{          micchi.ea2020-not,\n    author       = {Micchi, Gianluca and Gotham, Mark and Giraud, Mathieu},\n    year         = {2020},\n    title        = {Not All Roads Lead to Rome: Pitch Representation and\n                   Model Architecture for Automatic Harmonic Analysis},\n    abstract     = {Automatic harmonic analysis has been an enduring focus of\n                   the MIR community, and has enjoyed a particularly vigorous\n                   revival of interest in the machine-learning age. We focus\n                   here on the specific case of Roman numeral analysis which,\n                   by virtue of requiring key/functional information in\n                   addition to chords, may be viewed as an acutely\n                   challenging use case. We report on three main\n                   developments. First, we provide a new meta-corpus bringing\n                   together all existing Roman numeral analysis datasets;\n                   this offers greater scale and diversity, not only of the\n                   music represented, but also of human analytical\n                   viewpoints. Second, we examine best practices in the\n                   encoding of pitch, time, and harmony for machine learning\n                   tasks. The main contribution here is the introduction of\n                   full pitch spelling to such a system, an absolute must for\n                   the comprehensive study of musical harmony. Third, we\n                   devised and tested several neural network architectures\n                   and compared their relative accuracy. In the\n                   best-performing of these models, convolutional layers\n                   gather the local information needed to analyse the chord\n                   at a given moment while a recurrent part learns\n                   longer-range harmonic progressions. Altogether, our best\n                   representation and architecture produce a small but\n                   significant improvement on overall accuracy while\n                   simultaneously integrating full pitch spelling. This\n                   enables the system to retain important information from\n                   the musical sources and provide more meaningful\n                   predictions for any new input.},\n    doi          = {10.5334/tismir.45},\n    journal      = {Transactions of the International Society for Music\n                   Information Retrieval},\n    keywords     = {1,1 key,chords and functional harmony,computational\n                   musicology,corpus,functional harmony,introduction,is\n                   common to a,machine learning,motivation,pitch\n                   encoding,previous work,roman numeral analysis,some sense\n                   of,tonal harmony,very wide},\n    mendeley-tags= {computational musicology},\n    number       = {1},\n    pages        = {42--54},\n    volume       = {3}\n}\n\n
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\n Automatic harmonic analysis has been an enduring focus of the MIR community, and has enjoyed a particularly vigorous revival of interest in the machine-learning age. We focus here on the specific case of Roman numeral analysis which, by virtue of requiring key/functional information in addition to chords, may be viewed as an acutely challenging use case. We report on three main developments. First, we provide a new meta-corpus bringing together all existing Roman numeral analysis datasets; this offers greater scale and diversity, not only of the music represented, but also of human analytical viewpoints. Second, we examine best practices in the encoding of pitch, time, and harmony for machine learning tasks. The main contribution here is the introduction of full pitch spelling to such a system, an absolute must for the comprehensive study of musical harmony. Third, we devised and tested several neural network architectures and compared their relative accuracy. In the best-performing of these models, convolutional layers gather the local information needed to analyse the chord at a given moment while a recurrent part learns longer-range harmonic progressions. Altogether, our best representation and architecture produce a small but significant improvement on overall accuracy while simultaneously integrating full pitch spelling. This enables the system to retain important information from the musical sources and provide more meaningful predictions for any new input.\n
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\n \n\n \n \n \n \n \n \n A Systematic Literature Review on Computational Musicology.\n \n \n \n \n\n\n \n Mor, B.; Garhwal, S.; and Kumar, A.\n\n\n \n\n\n\n Archives of Computational Methods in Engineering, 27(3): 923–937. 2020.\n \n\n\n\n
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@Article{          mor.ea2020-systematic,\n    author       = {Mor, Bhavya and Garhwal, Sunita and Kumar, Ajay},\n    year         = {2020},\n    title        = {A Systematic Literature Review on Computational\n                   Musicology},\n    abstract     = {Heartbeat retains a musical rhythm and music speaks\n                   whenever words fail. This paper provides a systematic\n                   review of the papers related to computational musicology.\n                   This surveys 136 papers in more than 40 Journals and\n                   various Conference proceedings. The paper discusses the\n                   computational aspects of various music operations such as\n                   composition, analysis, retrieval, classification and\n                   implicit learning. The authors evaluate the literature\n                   based on multiple computational fields like formal\n                   grammar, hidden Markov model, n-gram, finite-state\n                   machine, finite-state transducer and artificial grammar\n                   learning. The paper aims to generate a comprehensive\n                   description of research on computational musicology.\n                   Throughout the paper, the significant trends in research\n                   on computational fields in music are summarized.},\n    doi          = {10.1007/s11831-019-09337-9},\n    isbn         = {0123456789},\n    issn         = {18861784},\n    journal      = {Archives of Computational Methods in Engineering},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    number       = {3},\n    pages        = {923--937},\n    publisher    = {Springer Netherlands},\n    url          = {https://doi.org/10.1007/s11831-019-09337-9},\n    volume       = {27}\n}\n\n
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\n Heartbeat retains a musical rhythm and music speaks whenever words fail. This paper provides a systematic review of the papers related to computational musicology. This surveys 136 papers in more than 40 Journals and various Conference proceedings. The paper discusses the computational aspects of various music operations such as composition, analysis, retrieval, classification and implicit learning. The authors evaluate the literature based on multiple computational fields like formal grammar, hidden Markov model, n-gram, finite-state machine, finite-state transducer and artificial grammar learning. The paper aims to generate a comprehensive description of research on computational musicology. Throughout the paper, the significant trends in research on computational fields in music are summarized.\n
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\n \n\n \n \n \n \n \n \n Harmony and Form in Brazilian Choro: A Corpus-Driven Approach to Musical Style Analysis.\n \n \n \n \n\n\n \n Moss, F. C.; de Souza, W. F.; and Rohrmeier, M.\n\n\n \n\n\n\n Journal of New Music Research, 0(0): 1–22. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"HarmonyPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          moss.ea2020-harmony,\n    author       = {Moss, Fabian Claude and de Souza, Willian Fernandes and\n                   Rohrmeier, Martin},\n    year         = {2020},\n    title        = {Harmony and Form in Brazilian Choro: A Corpus-Driven\n                   Approach to Musical Style Analysis},\n    doi          = {10.1080/09298215.2020.1797109},\n    issn         = {xxxx-xxxx},\n    journal      = {Journal of New Music Research},\n    keywords     = {Choro,choro,computational musicology,corpus\n                   study,form,harmony,musical style analysis},\n    mendeley-tags= {computational musicology},\n    number       = {0},\n    pages        = {1--22},\n    publisher    = {Taylor \\& Francis},\n    url          = {https://doi.org/09298215.2020.1797109},\n    volume       = {0}\n}\n\n
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\n \n\n \n \n \n \n \n \n SymPlot : A Web-Tool to Visualise Symbolic Musical Data.\n \n \n \n \n\n\n \n Muñoz-Lago, P.; Llorens, A.; Parada-Cabaleiro, E.; and Torrente, Á.\n\n\n \n\n\n\n In Proc. 24th International Converence Information Visualisation (IV), pages 515–521, Melbourne, Australia, 2020. \n \n\n\n\n
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@InProceedings{    munoz-lago.ea2020-symplot,\n    author       = {Mu{\\~{n}}oz-Lago, Paula and Llorens, Ana and\n                   Parada-Cabaleiro, Emilia and Torrente, {\\'{A}}lvaro},\n    year         = {2020},\n    title        = {SymPlot : A Web-Tool to Visualise Symbolic Musical Data},\n    address      = {Melbourne, Australia},\n    booktitle    = {Proc. 24th International Converence Information\n                   Visualisation (IV)},\n    doi          = {10.1109/IV51561.2020.00092},\n    isbn         = {9781728191348},\n    keywords     = {music visualization},\n    mendeley-tags= {music visualization},\n    pages        = {515--521},\n    url          = {https://conferences.computer.org/iv/pdfs/IV2020-5aDDWiHiJcr3O59ex2Ftp6/913400a515/913400a515.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n Mining Characteristic Patterns for Comparative Music Corpus Analysis.\n \n \n \n\n\n \n Neubarth, K.; and Conklin, D.\n\n\n \n\n\n\n Applied Sciences, 10(6). 2020.\n \n\n\n\n
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@Article{          neubarth.ea2020-mining,\n    author       = {Neubarth, Kerstin and Conklin, Darrell},\n    year         = {2020},\n    title        = {Mining Characteristic Patterns for Comparative Music\n                   Corpus Analysis},\n    doi          = {10.3390/app10061991},\n    journal      = {Applied Sciences},\n    keywords     = {characteristic pattern,computational\n                   ethnomusicology,discriminant pattern,music analysis with\n                   computers,music corpus analysis,native american\n                   music,pattern discovery},\n    mendeley-tags= {music analysis with computers},\n    number       = {6},\n    volume       = {10}\n}\n\n
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\n \n\n \n \n \n \n \n \n Compositional Systems: Overview and Applications.\n \n \n \n \n\n\n \n Pitombeira, L.\n\n\n \n\n\n\n MusMat - Brazilian Journal of Music and Mathematics, IV(1): 39–62. 2020.\n \n\n\n\n
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@Article{          pitombeira2020-compositional,\n    author       = {Pitombeira, Liduino},\n    year         = {2020},\n    title        = {Compositional Systems: Overview and Applications},\n    abstract     = {In this paper the theory of compositional systems is\n                   described in detail, taking as a starting point the\n                   theoretical framework inherent to systems science. The\n                   origins of this science and the definitions of its\n                   fundamental concepts are provided in the first part of the\n                   article, illustrated with musical examples. The central\n                   part of the article contains the definition of the concept\n                   of compositional system, its typology, and a series of\n                   tools that are useful for implementations. Finally, the\n                   design of three types of systems (open, semi-open and\n                   feedback) are carried out in order to produce small\n                   illustrative musical fragments.},\n    journal      = {MusMat - Brazilian Journal of Music and Mathematics},\n    keywords     = {compositional systems,music theory,probability,systemic\n                   modeling,systems science},\n    tags         = {music theory},\n    number       = {1},\n    pages        = {39--62},\n    url          = {https://musmat.org/wp-content/uploads/2020/06/07-Pitombeira.pdf},\n    volume       = {IV}\n}\n\n
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\n In this paper the theory of compositional systems is described in detail, taking as a starting point the theoretical framework inherent to systems science. The origins of this science and the definitions of its fundamental concepts are provided in the first part of the article, illustrated with musical examples. The central part of the article contains the definition of the concept of compositional system, its typology, and a series of tools that are useful for implementations. Finally, the design of three types of systems (open, semi-open and feedback) are carried out in order to produce small illustrative musical fragments.\n
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\n \n\n \n \n \n \n \n From Music Ontology towards Ethno-Music-Ontology.\n \n \n \n\n\n \n Proutskova, P.; Volk, A.; Fazekas, G.; and Heidarian, P.\n\n\n \n\n\n\n In Proceedings of 21st International Conference on Music Information Retrieval, pages 923–931, Montréal, Canada, 2020. \n \n\n\n\n
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@InProceedings{    proutskova.ea2020-from,\n    author       = {Proutskova, Polina and Volk, Anja and Fazekas,\n                   Gy{\\"{o}}rgy and Heidarian, Peyman},\n    year         = {2020},\n    title        = {From Music Ontology towards Ethno-Music-Ontology},\n    address      = {Montr{\\'{e}}al, Canada},\n    booktitle    = {Proceedings of 21st International Conference on Music\n                   Information Retrieval},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {923--931}\n}\n\n
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\n \n\n \n \n \n \n \n \n A quantitative study of pitch registers in string quartets opus 17, by Joseph Haydn.\n \n \n \n \n\n\n \n Sampaio, M.; de Oliveira, V. S.; Travassos, M.; and Castro, C.\n\n\n \n\n\n\n Musica Theorica, 5(1): 119–177. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          sampaio.ea2020-quantitative,\n    author       = {{Sampaio}, {Marcos da Silva} and de Oliveira, Vicente\n                   Sanches and Travassos, Matheus and Castro, Carla},\n    year         = {2020},\n    title        = {A quantitative study of pitch registers in string\n                   quartets opus 17, by Joseph Haydn},\n    abstract     = {In this paper, we present an exploratory study of the\n                   pitch registers on the string quartets Opus 17, by Joseph\n                   Haydn, according to a quantitative approach. This subject\n                   is relevant because the pitch registers studies have\n                   revealed noteworthy issues in the Musical Analysis area,\n                   the statistical techniques help to detect musical\n                   subtleties with a small potential for bias, and because on\n                   this corpus, Haydn has established standards for the\n                   string quartet genre. The pitch registers study allowed us\n                   to identify relevant musical aspects in the repertoire,\n                   understand the role of extreme registers in the form\n                   segmentation, and observe the prominence of the\n                   development and second theme sections, and the feasibility\n                   of the quantitative methods. We present a brief\n                   theoretical foundation, the methodological framework, the\n                   results of the investigation on the quartets' instrument\n                   pitches, a discussion about these results, and the\n                   conclusions.},\n    journal      = {Musica Theorica},\n    keywords     = {Digital Musicology,Joseph Haydn,Pitch\n                   register,Quantitative analysis,String\n                   quartet,computational musicology},\n    mendeley-tags= {computational musicology},\n    number       = {1},\n    pages        = {119--177},\n    url          = {http://revistamusicatheorica.tema.mus.br/index.php/musica-theorica/article/view/128},\n    volume       = {5}\n}\n\n
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\n In this paper, we present an exploratory study of the pitch registers on the string quartets Opus 17, by Joseph Haydn, according to a quantitative approach. This subject is relevant because the pitch registers studies have revealed noteworthy issues in the Musical Analysis area, the statistical techniques help to detect musical subtleties with a small potential for bias, and because on this corpus, Haydn has established standards for the string quartet genre. The pitch registers study allowed us to identify relevant musical aspects in the repertoire, understand the role of extreme registers in the form segmentation, and observe the prominence of the development and second theme sections, and the feasibility of the quantitative methods. We present a brief theoretical foundation, the methodological framework, the results of the investigation on the quartets' instrument pitches, a discussion about these results, and the conclusions.\n
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\n \n\n \n \n \n \n \n \n A cluster analysis of harmony in the McGill Billboard dataset.\n \n \n \n \n\n\n \n Shaffer, K.; Vasiete, E.; Jacquez, B.; Davis, A.; Escalante, D.; Hicks, C.; McCann, J.; Noufi, C.; and Salminen, P.\n\n\n \n\n\n\n Empirical Musicology Review, 14(3-4): 146. jul 2020.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          shaffer.ea2020-cluster,\n    author       = {Shaffer, Kris and Vasiete, Esther and Jacquez, Brandon\n                   and Davis, Aaron and Escalante, Diego and Hicks, Calvin\n                   and McCann, Joshua and Noufi, Camille and Salminen, Paul},\n    year         = {2020},\n    title        = {A cluster analysis of harmony in the McGill Billboard\n                   dataset},\n    abstract     = {We set out to perform a cluster analysis of harmonic\n                   structures (specifically, chord-to-chord transitions) in\n                   the McGill Billboard dataset, to determine whether there\n                   is evidence of multiple harmonic grammars and practices in\n                   the corpus, and if so, what the optimal division of songs,\n                   according to those harmonic grammars, is. We define\n                   optimal as providing meaningful, specific information\n                   about the harmonic practices of songs in the cluster, but\n                   being general enough to be used as a guide to songwriting\n                   and predictive listening. We test two hypotheses in our\n                   cluster analysis — first that 5–9 clusters would be\n                   optimal, based on the work of Walter Everett (2004), and\n                   second that 15 clusters would be optimal, based on a set\n                   of user-generated genre tags reported by Hendrik Schreiber\n                   (2015). We subjected the harmonic structures for each song\n                   in the corpus to a K-means cluster analysis. We conclude\n                   that the optimal clustering solution is likely to be\n                   within the 5--8 cluster range. We also propose that a map\n                   of cluster types emerging as the number of clusters\n                   increases from one to eight constitutes a greater aid to\n                   our understanding of how various harmonic practices,\n                   styles, and sub-styles comprise the McGill Billboard\n                   dataset.},\n    doi          = {10.18061/emr.v14i3-4.5576},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {McGill Billboard dataset,cluster analysis,harmonic\n                   syntax,machine learning,music analysis with\n                   computers,pop/rock,rock,transitional\n                   probability,visualization},\n    mendeley-tags= {music analysis with computers},\n    month        = {jul},\n    number       = {3-4},\n    pages        = {146},\n    url          = {https://emusicology.org/article/view/5576},\n    volume       = {14}\n}\n\n
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\n We set out to perform a cluster analysis of harmonic structures (specifically, chord-to-chord transitions) in the McGill Billboard dataset, to determine whether there is evidence of multiple harmonic grammars and practices in the corpus, and if so, what the optimal division of songs, according to those harmonic grammars, is. We define optimal as providing meaningful, specific information about the harmonic practices of songs in the cluster, but being general enough to be used as a guide to songwriting and predictive listening. We test two hypotheses in our cluster analysis — first that 5–9 clusters would be optimal, based on the work of Walter Everett (2004), and second that 15 clusters would be optimal, based on a set of user-generated genre tags reported by Hendrik Schreiber (2015). We subjected the harmonic structures for each song in the corpus to a K-means cluster analysis. We conclude that the optimal clustering solution is likely to be within the 5–8 cluster range. We also propose that a map of cluster types emerging as the number of clusters increases from one to eight constitutes a greater aid to our understanding of how various harmonic practices, styles, and sub-styles comprise the McGill Billboard dataset.\n
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\n \n\n \n \n \n \n \n SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python.\n \n \n \n\n\n \n Virtanen, P.; Gommers, R.; Oliphant, T. E.; Haberland, M.; Reddy, T.; Cournapeau, D.; Burovski, E.; Peterson, P.; Weckesser, W.; Bright, J.; van der Walt , S. J.; Brett, M.; Wilson, J.; Millman, K. J.; Mayorov, N.; Nelson, A. R. J.; Jones, E.; Kern, R.; Larson, E.; Carey, C J; Polat, İ.; Feng, Y.; Moore, E. W.; VanderPlas, J.; Laxalde, D.; Perktold, J.; Cimrman, R.; Henriksen, I.; Quintero, E. A.; Harris, C. R.; Archibald, A. M.; Ribeiro, A. H.; Pedregosa, F.; van Mulbregt , P.; and SciPy 1.0 Contributors\n\n\n \n\n\n\n Nature Methods, 17: 261–272. 2020.\n \n\n\n\n
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@Article{          virtanen.ea2020-scipy,\n    author       = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E.\n                   and Haberland, Matt and Reddy, Tyler and Cournapeau, David\n                   and Burovski, Evgeni and Peterson, Pearu and Weckesser,\n                   Warren and Bright, Jonathan and {van der Walt}, St{\\'e}fan\n                   J. and Brett, Matthew and Wilson, Joshua and Millman, K.\n                   Jarrod and Mayorov, Nikolay and Nelson, Andrew R. J. and\n                   Jones, Eric and Kern, Robert and Larson, Eric and Carey, C\n                   J and Polat, {\\.I}lhan and Feng, Yu and Moore, Eric W. and\n                   {VanderPlas}, Jake and Laxalde, Denis and Perktold, Josef\n                   and Cimrman, Robert and Henriksen, Ian and Quintero, E. A.\n                   and Harris, Charles R. and Archibald, Anne M. and Ribeiro,\n                   Ant{\\^o}nio H. and Pedregosa, Fabian and {van Mulbregt},\n                   Paul and {SciPy 1.0 Contributors}},\n    year         = {2020},\n    title        = {{SciPy} 1.0: Fundamental Algorithms for Scientific\n                   Computing in Python},\n    journal      = {Nature Methods},\n    volume       = {17},\n    pages        = {261--272},\n    adsurl       = {https://rdcu.be/b08Wh},\n    doi          = {10.1038/s41592-019-0686-2}\n}\n\n
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\n \n\n \n \n \n \n \n \n Learning Sonata Form Structure on Mozart's String Quartets.\n \n \n \n \n\n\n \n Allegraud, P.; Bigo, L.; Feisthauer, L.; Giraud, M.; Groult, R.; Leguy, E.; and Levé, F.\n\n\n \n\n\n\n Transactions of the International Society for Music Information Retrieval, 2(1): 82–96. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"LearningPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          allegraud.ea2019-learning,\n    author       = {Allegraud, Pierre and Bigo, Louis and Feisthauer, Laurent\n                   and Giraud, Mathieu and Groult, Richard and Leguy,\n                   Emmanuel and Lev{\\'{e}}, Florence},\n    year         = {2019},\n    title        = {Learning Sonata Form Structure on Mozart's String\n                   Quartets},\n    doi          = {10.5334/tismir.27},\n    issn         = {2514-3298},\n    journal      = {Transactions of the International Society for Music\n                   Information Retrieval},\n    keywords     = {computational music analysis,music analysis with\n                   computers,music structure,musical form,sonata form},\n    mendeley-tags= {music analysis with computers},\n    number       = {1},\n    pages        = {82--96},\n    url          = {http://transactions.ismir.net/articles/10.5334/tismir.27/},\n    volume       = {2}\n}\n\n
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\n \n\n \n \n \n \n \n Glossário de Estatística.\n \n \n \n\n\n \n Assis, J. P. d.; Sousa, R. P. d.; and Dias, C. T. d. S.\n\n\n \n\n\n\n EDUFERSA, Mossoró, RN, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Book{             assis.ea2019-glossario,\n    author       = {Assis, Janilson Pinheiro de and Sousa, Roberto Pequeno de\n                   and Dias, Carlos Tadeu dos Santos},\n    year         = {2019},\n    title        = {Gloss\\'{a}rio de {Estat\\'{i}stica}},\n    address      = {Mossor\\'{o}, RN},\n    isbn         = {978-85-5757-104-4},\n    language     = {pt},\n    publisher    = {EDUFERSA}\n}\n\n
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\n \n\n \n \n \n \n \n \n A Computational Model of Immanent Accent Salience in Tonal Music.\n \n \n \n \n\n\n \n Bisesi, E.; Friberg, A.; and Parncutt, R.\n\n\n \n\n\n\n Frontiers in Psychology, 10: 1–19. mar 2019.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          bisesi.ea2019-computational,\n    author       = {Bisesi, Erica and Friberg, Anders and Parncutt, Richard},\n    year         = {2019},\n    title        = {A Computational Model of Immanent Accent Salience in\n                   Tonal Music},\n    abstract     = {We describe the first stage of a two-stage semi-\n                   algorithmic approach to music performance rendering. In\n                   the first stage, we estimate the perceptual salience of\n                   immanent accents (phrasing, metrical, melodic, harmon- ic)\n                   in the musical score. In the second, we manipulate timing,\n                   dynamics and other performance parameters in the vicinity\n                   of immanent accents (e. g., getting slower and/or louder\n                   near an accent). Phrasing and metrical accents emerge from\n                   the hierarchical structure of phras- ing and meter; their\n                   salience depends on the hierarchical levels that they\n                   demarcate, and their salience. Melodic accents follow\n                   melodic leaps; they are strongest at con- tour peaks and\n                   (to a lesser extent) valleys; and their sali- ence depends\n                   on the leap interval and the distance of the target tone\n                   from the local mean pitch. Harmonic accents depend on\n                   local dissonance (roughness, non-harmonicity,\n                   non-diatonicity) and chord/key changes. The algorithm is\n                   under development and is being tested by comparing its\n                   predictions with music analyses, recorded performances and\n                   listener evaluations. 1.},\n    address      = {Stockolm, Sweden},\n    doi          = {10.3389/fpsyg.2019.00317},\n    issn         = {1664-1078},\n    journal      = {Frontiers in Psychology},\n    keywords     = {Computational modeling,Immanent accents,Music\n                   analysis,Music expression,Salience,computational\n                   musicology,music analysis with computers},\n    mendeley-tags= {computational musicology,music analysis with computers},\n    month        = {mar},\n    pages        = {1--19},\n    url          = {https://www.frontiersin.org/article/10.3389/fpsyg.2019.00317/full},\n    volume       = {10}\n}\n\n
\n
\n\n\n
\n We describe the first stage of a two-stage semi- algorithmic approach to music performance rendering. In the first stage, we estimate the perceptual salience of immanent accents (phrasing, metrical, melodic, harmon- ic) in the musical score. In the second, we manipulate timing, dynamics and other performance parameters in the vicinity of immanent accents (e. g., getting slower and/or louder near an accent). Phrasing and metrical accents emerge from the hierarchical structure of phras- ing and meter; their salience depends on the hierarchical levels that they demarcate, and their salience. Melodic accents follow melodic leaps; they are strongest at con- tour peaks and (to a lesser extent) valleys; and their sali- ence depends on the leap interval and the distance of the target tone from the local mean pitch. Harmonic accents depend on local dissonance (roughness, non-harmonicity, non-diatonicity) and chord/key changes. The algorithm is under development and is being tested by comparing its predictions with music analyses, recorded performances and listener evaluations. 1.\n
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\n \n\n \n \n \n \n \n Estatística Prática para Cientista de Dados.\n \n \n \n\n\n \n Bruce, P.\n\n\n \n\n\n\n Alta Books, Rio de Janeiro, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             bruce2019-estatistica,\n    author       = {Bruce, Peter},\n    year         = {2019},\n    title        = {Estat{\\'{i}}stica Pr{\\'{a}}tica para Cientista de Dados},\n    address      = {Rio de Janeiro},\n    isbn         = {9788490225370},\n    keywords     = {statistics},\n    mendeley-tags= {statistics},\n    publisher    = {Alta Books}\n}\n\n
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\n \n\n \n \n \n \n \n Alternative measures: A musicologist workbench for popular music.\n \n \n \n\n\n \n Clark, B.; and Arthur, C.\n\n\n \n\n\n\n In Proceedings of the Sound and Music Computing Conferences, pages 407–414, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InProceedings{    clark.ea2019-alternative,\n    author       = {Clark, Beach and Arthur, Claire},\n    year         = {2019},\n    title        = {Alternative measures: A musicologist workbench for\n                   popular music},\n    abstract     = {The objective of this project is to create a digital\n                   “workbench” for quantitative analysis of popular\n                   music. The workbench is a collection of tools and data\n                   that allow for efficient and effective analysis of popular\n                   music. This project integrates software from pre-existing\n                   analytical tools including music21 but adds methods for\n                   collecting data about popular music. The workbench\n                   includes tools that allow analysts to compare data from\n                   multiple sources. Our working prototype of the workbench\n                   contains several novel analytical tools which have the\n                   potential to generate new musicological insights through\n                   the combination of various datasets. This paper\n                   demonstrates some of the currently available tools as well\n                   as several sample analyses and features computed from this\n                   data that support trend analysis. A future release of the\n                   workbench will include a user-friendly UI for\n                   non-programmers.},\n    booktitle    = {Proceedings of the Sound and Music Computing\n                   Conferences},\n    isbn         = {9788409085187},\n    issn         = {25183672},\n    pages        = {407--414}\n}\n\n
\n
\n\n\n
\n The objective of this project is to create a digital “workbench” for quantitative analysis of popular music. The workbench is a collection of tools and data that allow for efficient and effective analysis of popular music. This project integrates software from pre-existing analytical tools including music21 but adds methods for collecting data about popular music. The workbench includes tools that allow analysts to compare data from multiple sources. Our working prototype of the workbench contains several novel analytical tools which have the potential to generate new musicological insights through the combination of various datasets. This paper demonstrates some of the currently available tools as well as several sample analyses and features computed from this data that support trend analysis. A future release of the workbench will include a user-friendly UI for non-programmers.\n
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\n \n\n \n \n \n \n \n HUMDRUMR : a new take on an old approach to Computational Musicology.\n \n \n \n\n\n \n Condit-Schultz, N.; and Arthur, C.\n\n\n \n\n\n\n In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 715–722, Delft, Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    condit-schultz.ea2019-humdrumr,\n    author       = {Condit-Schultz, Nathaniel and Arthur, Claire},\n    year         = {2019},\n    title        = {HUMDRUMR : a new take on an old approach to Computational\n                   Musicology},\n    address      = {Delft, Netherlands},\n    booktitle    = {Proceedings of the 20th International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {715--722}\n}\n\n
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\n \n\n \n \n \n \n \n Learning, Probability and Logic: Toward a Unified Approach for Content-Based Music Information Retrieval.\n \n \n \n\n\n \n Crayencour, H.; and Cella, C.\n\n\n \n\n\n\n Frontiers in Digital Humanities, 6(April): 1–25. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          crayencour.ea2019-learning,\n    author       = {Crayencour, Helene-Camille and Cella, Carmine-Emanuele},\n    year         = {2019},\n    title        = {Learning, Probability and Logic: Toward a Unified\n                   Approach for Content-Based Music Information Retrieval},\n    abstract     = {Within the last fifteen years, the field of Music\n                   Information Retrieval (MIR) has made tremendous progress\n                   in the development of algorithms for organizing and\n                   analyzing the ever-increasing large and varied amount of\n                   music and music-related data available digitally. However,\n                   the development of content-based methods to enable or\n                   improve multimedia retrieval still remains a central\n                   challenge. In this perspective paper, we critically look\n                   at the problem of automatic chord estimation from audio\n                   recordings as a case study of content-based algorithms,\n                   and point out several bottlenecks in current approaches:\n                   expressiveness and flexibility are obtained to the expense\n                   of robustness and vice-versa; available multimodal sources\n                   of information are little exploited; modeling\n                   multi-faceted and strongly interrelated musical\n                   information is limited with current architectures; models\n                   are typically restricted to short-term analysis that does\n                   not account for the hierarchical temporal structure of\n                   musical signals. Dealing with music data requires the\n                   ability to handle both uncertainty and complex relational\n                   structure at multiple levels of representation.\n                   Traditional approaches have generally treated these two\n                   aspects separately, probability and learning being the\n                   standard way to represent uncertainty in knowledge, while\n                   logical representation being the standard way to represent\n                   knowledge and complex relational information. We advocate\n                   that the identified hurdles of current approaches could be\n                   overcome by recent developments in the area of Statistical\n                   Relational Artificial Intelligence (StarAI) that unifies\n                   probability, logic and (deep) learning. We show that\n                   existing approaches used in MIR find powerful extensions\n                   and unifications in StarAI, and we explain why we think it\n                   is time to consider the new perspectives offered by this\n                   promising research field.},\n    doi          = {10.3389/fdigh.2019.00006},\n    issn         = {2297-2668},\n    journal      = {Frontiers in Digital Humanities},\n    keywords     = {audio,chord recognition,content-based,mir,music\n                   information retrieval,music information retrieval\n                   (MIR),statistical relational artificial,statistical\n                   relational artificial intelligence},\n    mendeley-tags= {music information retrieval},\n    number       = {April},\n    pages        = {1--25},\n    volume       = {6}\n}\n\n
\n
\n\n\n
\n Within the last fifteen years, the field of Music Information Retrieval (MIR) has made tremendous progress in the development of algorithms for organizing and analyzing the ever-increasing large and varied amount of music and music-related data available digitally. However, the development of content-based methods to enable or improve multimedia retrieval still remains a central challenge. In this perspective paper, we critically look at the problem of automatic chord estimation from audio recordings as a case study of content-based algorithms, and point out several bottlenecks in current approaches: expressiveness and flexibility are obtained to the expense of robustness and vice-versa; available multimodal sources of information are little exploited; modeling multi-faceted and strongly interrelated musical information is limited with current architectures; models are typically restricted to short-term analysis that does not account for the hierarchical temporal structure of musical signals. Dealing with music data requires the ability to handle both uncertainty and complex relational structure at multiple levels of representation. Traditional approaches have generally treated these two aspects separately, probability and learning being the standard way to represent uncertainty in knowledge, while logical representation being the standard way to represent knowledge and complex relational information. We advocate that the identified hurdles of current approaches could be overcome by recent developments in the area of Statistical Relational Artificial Intelligence (StarAI) that unifies probability, logic and (deep) learning. We show that existing approaches used in MIR find powerful extensions and unifications in StarAI, and we explain why we think it is time to consider the new perspectives offered by this promising research field.\n
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\n \n\n \n \n \n \n \n \n Modeling and learning structural breaks in sonata forms.\n \n \n \n \n\n\n \n Feisthauer, L.; Bigo, L.; and Giraud, M.\n\n\n \n\n\n\n In Proc. International Society for Music Information Retrieval Conference 2019, Utrecht, Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n \n \"ModelingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    feisthauer.ea2019-modeling,\n    author       = {Feisthauer, Laurent and Bigo, Louis and Giraud, Mathieu},\n    year         = {2019},\n    title        = {Modeling and learning structural breaks in sonata forms},\n    abstract     = {Expositions of Sonata Forms are structured towards two\n                   cadential goals, one being the Medial Caesura (MC). The MC\n                   is a gap in the musical texture between the Transition\n                   zone (TR) and the Secondary thematic zone (S). It appears\n                   as a climax of energy accumulation initiated by the TR,\n                   dividing the Exposition in two parts. We introduce\n                   high-level features relevant to formalize this energy gain\n                   and to identify MCs. These features concern rhythmic,\n                   harmonic and textural aspects of the music and\n                   characterize either the MC, its preparation or the texture\n                   contrast between TR and S. They are used to train a LSTM\n                   neural network on a corpus of 27 movements of string\n                   quartets written by Mozart. The model correctly locates\n                   the MCs on 14 movements within a leave-one-piece-out\n                   validation strategy. We discuss these results and how the\n                   network manages to model such structural breaks.},\n    address      = {Utrecht, Netherlands},\n    booktitle    = {Proc. International Society for Music Information\n                   Retrieval Conference 2019},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    url          = {https://hal.archives-ouvertes.fr/hal-02162936}\n}\n\n
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\n\n\n
\n Expositions of Sonata Forms are structured towards two cadential goals, one being the Medial Caesura (MC). The MC is a gap in the musical texture between the Transition zone (TR) and the Secondary thematic zone (S). It appears as a climax of energy accumulation initiated by the TR, dividing the Exposition in two parts. We introduce high-level features relevant to formalize this energy gain and to identify MCs. These features concern rhythmic, harmonic and textural aspects of the music and characterize either the MC, its preparation or the texture contrast between TR and S. They are used to train a LSTM neural network on a corpus of 27 movements of string quartets written by Mozart. The model correctly locates the MCs on 14 movements within a leave-one-piece-out validation strategy. We discuss these results and how the network manages to model such structural breaks.\n
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\n \n\n \n \n \n \n \n \n Visualizing music similarity: clustering and mapping 500 classical music composers.\n \n \n \n \n\n\n \n Georges, P.; and Nguyen, N.\n\n\n \n\n\n\n Scientometrics, (0123456789). 2019.\n \n\n\n\n
\n\n\n\n \n \n \"VisualizingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          georges.ea2019-visualizing,\n    author       = {Georges, Patrick and Nguyen, Ngoc},\n    year         = {2019},\n    title        = {Visualizing music similarity: clustering and mapping 500\n                   classical music composers},\n    doi          = {10.1007/s11192-019-03166-0},\n    isbn         = {0123456789},\n    issn         = {0138-9130},\n    journal      = {Scientometrics},\n    keywords     = {Canonical correlation,Dendrograms,Hierarchical\n                   clustering,Mapping classical music\n                   composers,Multidimensional scaling,Music information\n                   retrieval,Similarity measures,canonical\n                   correlation,dendrograms,hierarchical\n                   clustering,information retrieval,mapping classical music\n                   composers,multidimensional scaling,music,music\n                   similarity,similarity measures},\n    mendeley-tags= {music similarity},\n    number       = {0123456789},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/s11192-019-03166-0}\n}\n\n
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\n \n\n \n \n \n \n \n Mãos à Obra Aprendizado de Máquina com Scikit-Learn & TensorFlow: Conceitos, Ferramentas e Técnicas para a Construção de Sistemas Inteligentes.\n \n \n \n\n\n \n Géron, A.\n\n\n \n\n\n\n Alta Books, Rio de Janeiro, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@Book{             geron2019-maos,\n    author       = {G{\\'{e}}ron, Aur{\\'{e}}lion},\n    year         = {2019},\n    title        = {M{\\~{a}}os {\\`{a}} Obra Aprendizado de M{\\'{a}}quina com\n                   Scikit-Learn & TensorFlow: Conceitos, Ferramentas e\n                   T{\\'{e}}cnicas para a Constru{\\c{c}}{\\~{a}}o de Sistemas\n                   Inteligentes},\n    address      = {Rio de Janeiro},\n    isbn         = {978-85-508-03814},\n    keywords     = {Aprendizado de M{\\'{a}}quina,Ci{\\^{e}}ncia da\n                   computa{\\c{c}}{\\~{a}}o},\n    pages        = {576},\n    publisher    = {Alta Books}\n}\n\n
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\n \n\n \n \n \n \n \n Taking Form: a representation standard, conversion code, and example corpus for recording, visualizing, and studying analysis of musical form.\n \n \n \n\n\n \n Gotham, M.; and Ireland, M. T\n\n\n \n\n\n\n In Proceedings of the 20th International Society for Music Information Retrieval Conference, Delft, Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    gotham.ea2019-taking,\n    author       = {Gotham, Mark and Ireland, Matthew T},\n    year         = {2019},\n    title        = {Taking Form: a representation standard, conversion code,\n                   and example corpus for recording, visualizing, and\n                   studying analysis of musical form},\n    address      = {Delft, Netherlands},\n    booktitle    = {Proceedings of the 20th International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology}\n}\n\n
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\n \n\n \n \n \n \n \n \n Minor-Mode Sonata-Form Dynamics in Haydn's String Quartets.\n \n \n \n \n\n\n \n Hall, M. J.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 9(1). 2019.\n \n\n\n\n
\n\n\n\n \n \n \"Minor-ModePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          hall2019-minor-mode,\n    author       = {Hall, Matthew J.},\n    year         = {2019},\n    title        = {Minor-Mode Sonata-Form Dynamics in Haydn's String\n                   Quartets},\n    abstract     = {The predominance of major-mode works in the repertoire\n                   corresponds with the view that minor-mode works are\n                   exceptions to a major-mode norm. For example, Charles\n                   Rosen's Sonata Forms, James Hepokoski and Warren Darcy's\n                   Sonata Theory, and William Caplin's Classical Form all\n                   theorize from the perspective of a major-mode default.\n                   Although certain canonical minor-mode works have received\n                   sustained scholarly attention, minor-mode sonata style in\n                   general is less often studied. Despite their relatively\n                   fewer numbers, minor-mode works comprise a substantial\n                   corpus. Among the string quartets of Joseph Haydn, the\n                   minor mode is represented in every opus beginning with Op.\n                   9; even Haydn's last unfinished quartet, “Op. 103,”\n                   was to be in the minor. The},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    url          = {https://www.rit.edu/affiliate/haydn/sites/rit.edu.affiliate.haydn/files/article_pdfs/Hall.MinorModeQuartet\n                   for PDF.pdf},\n    volume       = {9}\n}\n\n
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\n The predominance of major-mode works in the repertoire corresponds with the view that minor-mode works are exceptions to a major-mode norm. For example, Charles Rosen's Sonata Forms, James Hepokoski and Warren Darcy's Sonata Theory, and William Caplin's Classical Form all theorize from the perspective of a major-mode default. Although certain canonical minor-mode works have received sustained scholarly attention, minor-mode sonata style in general is less often studied. Despite their relatively fewer numbers, minor-mode works comprise a substantial corpus. Among the string quartets of Joseph Haydn, the minor mode is represented in every opus beginning with Op. 9; even Haydn's last unfinished quartet, “Op. 103,” was to be in the minor. The\n
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\n \n\n \n \n \n \n \n Algorithmic Ability to Predict the Musical Future: Datasets and Evaluation.\n \n \n \n\n\n \n Janssen, B.; Collins, T.; and Ren, I. Y.\n\n\n \n\n\n\n In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 208–215, Delft, Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    janssen.ea2019-algorithmic,\n    author       = {Janssen, Berit and Collins, Tom and Ren, Iris Yuping},\n    year         = {2019},\n    title        = {Algorithmic Ability to Predict the Musical Future:\n                   Datasets and Evaluation},\n    address      = {Delft, Netherlands},\n    booktitle    = {Proceedings of the 20th International Society for Music\n                   Information Retrieval Conference},\n    doi          = {10.5281/zenodo.3527780},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval},\n    pages        = {208--215}\n}\n\n
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\n \n\n \n \n \n \n \n \n The Structure of Morphological Space.\n \n \n \n \n\n\n \n Kant, D.; and Polansky, L.\n\n\n \n\n\n\n Perspectives of New Music, 57(1): 441–498. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Article{          kant.ea2019-structure,\n    author       = {Kant, David and Polansky, Larry},\n    year         = {2019},\n    title        = {The {Structure} of {Morphological} {Space}},\n    volume       = {57},\n    issn         = {2325-7180},\n    url          = {https://muse.jhu.edu/article/778501},\n    doi          = {10.1353/pnm.2019.0022},\n    language     = {en},\n    number       = {1},\n    urldate      = {2023-02-23},\n    journal      = {Perspectives of New Music},\n    tags         = {musical contour},\n    pages        = {441--498}\n}\n\n
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\n \n\n \n \n \n \n \n \n Annotator subjectivity in harmony annotations of popular music.\n \n \n \n \n\n\n \n Koops, H. V.; de Haas, W. B.; Burgoyne, J. A.; Bransen, J.; Kent-Muller, A.; and Volk, A.\n\n\n \n\n\n\n Journal of New Music Research, 0(0): 1–21. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"AnnotatorPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          koops.ea2019-annotator,\n    author       = {Koops, Hendrik Vincent and de Haas, W. Bas and Burgoyne,\n                   John Ashley and Bransen, Jeroen and Kent-Muller, Anna and\n                   Volk, Anja},\n    year         = {2019},\n    title        = {Annotator subjectivity in harmony annotations of popular\n                   music},\n    doi          = {10.1080/09298215.2019.1613436},\n    issn         = {xxxx-xxxx},\n    journal      = {Journal of New Music Research},\n    keywords     = {Annotator subjectivity,annotator\n                   subjectivity,harmony,inter-rater,inter-rater\n                   agreement,music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {0},\n    pages        = {1--21},\n    publisher    = {Taylor \\& Francis},\n    url          = {https://doi.org/09298215.2019.1613436},\n    volume       = {0}\n}\n\n
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\n \n\n \n \n \n \n \n A Deep Learning Approach to generate Beethoven's 10th Symphony.\n \n \n \n\n\n \n Lago, P. M.\n\n\n \n\n\n\n Ph.D. Thesis, Universidad Complutense de Madrid, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@PhDThesis{        lago2019-deep,\n    author       = {Lago, Paula Mu{\\~{n}}oz},\n    year         = {2019},\n    title        = {A Deep Learning Approach to generate Beethoven's 10th\n                   Symphony},\n    keywords     = {machine learning},\n    mendeley-tags= {machine learning},\n    school       = {Universidad Complutense de Madrid},\n    type         = {Trabajo de Fin de Grado}\n}\n\n
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\n \n\n \n \n \n \n \n What Constitutes a Musical Pattern ?.\n \n \n \n\n\n \n Melkonian, O.; Ren, I. Y.; Swierstra, W.; and Volk, A.\n\n\n \n\n\n\n In Proceedings of the 7th ACM SIGPLAN International Workshop on Functional Art, Music, Modeling, and Design (FARM '19), Berlin, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@InProceedings{    melkonian.ea2019-what,\n    author       = {Melkonian, Orestis and Ren, Iris Yuping and Swierstra,\n                   Wouster and Volk, Anja},\n    year         = {2019},\n    title        = {What Constitutes a Musical Pattern ?},\n    address      = {Berlin},\n    booktitle    = {Proceedings of the 7th ACM SIGPLAN International Workshop\n                   on Functional Art, Music, Modeling, and Design (FARM\n                   '19)},\n    keywords     = {19,2019,2019 association for computing,august\n                   23,berlin,clustering,contravariance,edit\n                   distance,evaluation,farm,germany,machinery,music analysis\n                   with computers,musical patterns,transformation},\n    mendeley-tags= {music analysis with computers}\n}\n\n
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\n \n\n \n \n \n \n \n Applied Time Series Analysis: A Practical Guide to Modeling and Forecasting Terence.\n \n \n \n\n\n \n Mills, T. C.\n\n\n \n\n\n\n Academic Press, London, UK, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Book{             mills2019-applied,\n    author       = {Mills, Terence C.},\n    year         = {2019},\n    title        = {Applied Time Series Analysis: A Practical Guide to\n                   Modeling and Forecasting Terence},\n    address      = {London, UK},\n    isbn         = {9789048187676},\n    issn         = {18761100},\n    keywords     = {Autoregression,Basic characteristics,Estimation of\n                   correlation,Mathematical models,Time series\n                   analysis,statistics},\n    mendeley-tags= {statistics},\n    publisher    = {Academic Press}\n}\n\n
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\n \n\n \n \n \n \n \n \n Statistical characteristics of tonal harmony: a corpus study of Beethoven's string quartets.\n \n \n \n \n\n\n \n Moss, F. C.; Neuwirth, M.; Harasim, D.; and Rohrmeier, M.\n\n\n \n\n\n\n PLoS ONE,1–16. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"StatisticalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          moss.ea2019-statistical,\n    author       = {Moss, Fabian Claude and Neuwirth, Markus and Harasim,\n                   Daniel and Rohrmeier, Martin},\n    year         = {2019},\n    title        = {Statistical characteristics of tonal harmony: a corpus\n                   study of Beethoven's string quartets},\n    doi          = {10.1371/journal.pone.0217242},\n    isbn         = {1111111111},\n    journal      = {PLoS ONE},\n    pages        = {1--16},\n    url          = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217242}\n}\n\n
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\n \n\n \n \n \n \n \n Transitions of Tonality: A Model-Based Corpus Study.\n \n \n \n\n\n \n Moss, F. C.\n\n\n \n\n\n\n Ph.D. Thesis, École Polytehcnique Fédérale de Lausanne, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        moss2019-transitions,\n    author       = {Moss, Fabian Claude},\n    year         = {2019},\n    title        = {Transitions of Tonality: A Model-Based Corpus Study},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    school       = {{\\'{E}}cole Polytehcnique F{\\'{e}}d{\\'{e}}rale de Lausanne},\n    type         = {Ph.D. Thesis}\n}\n\n
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\n \n\n \n \n \n \n \n Contributing to New Musicological Theories with Computational Methods: The Case of Centonization in Arab-Andalusian Music.\n \n \n \n\n\n \n Nuttall, T.; García-Casado, M.; Núñez-Tarifa, V.; Repetto, R. C.; and Serra, X.\n\n\n \n\n\n\n In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 223–228, Delft, Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    nuttall.ea2019-contributing,\n    author       = {Nuttall, Thomas and Garc{\\'{i}}a-Casado, Miguel and\n                   N{\\'{u}}{\\~{n}}ez-Tarifa, V{\\'{i}}ctor and Repetto, Rafael\n                   Caro and Serra, Xavier},\n    year         = {2019},\n    title        = {Contributing to New Musicological Theories with\n                   Computational Methods: The Case of Centonization in\n                   Arab-Andalusian Music},\n    abstract     = {Arab-Andalusian music was formed in the medieval Islamic\n                   territories of Iberian Peninsula, drawing on local\n                   traditions and assuming Arabic influences. The expert\n                   performer and researcher of the Moroccan tradition of this\n                   music, Amin Chaachoo, is developing a theory, whose last\n                   formulation was recently published in La Mu-sique\n                   Hispano-Arabe, al-Ala (2016), which argues that\n                   centonization, a melodic composition technique used in\n                   Gregorian chant, was also utilized for the creation of\n                   this repertoire. In this paper we aim to contribute to\n                   Chaachoo's theory by means of tf-idf analysis. A highorder\n                   n-gram model is applied to a corpus of 149 prescriptive\n                   transcriptions of heterophonic recordings, representing\n                   each as an unordered multiset of patterns. Computing the\n                   tf-idf statistic of each pattern in this corpus provides a\n                   means by which we can rank and compare motivic content\n                   across nawabāt, distinct musical forms of the tradition.\n                   For each nawba, an empirical comparison is made between\n                   patterns identified as significant via our approach and\n                   those proposed by Chaachoo. Ultimately we observe\n                   considerable agreement between the two pattern sets and go\n                   further in proposing new, unique and as yet undocumented\n                   patterns that occur at least as frequently and with at\n                   least as much importance as those in Chaachoo's\n                   proposals.},\n    address      = {Delft, Netherlands},\n    booktitle    = {Proceedings of the 20th International Society for Music\n                   Information Retrieval Conference},\n    doi          = {10.5281/zenodo.3527784},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval},\n    pages        = {223--228}\n}\n\n
\n
\n\n\n
\n Arab-Andalusian music was formed in the medieval Islamic territories of Iberian Peninsula, drawing on local traditions and assuming Arabic influences. The expert performer and researcher of the Moroccan tradition of this music, Amin Chaachoo, is developing a theory, whose last formulation was recently published in La Mu-sique Hispano-Arabe, al-Ala (2016), which argues that centonization, a melodic composition technique used in Gregorian chant, was also utilized for the creation of this repertoire. In this paper we aim to contribute to Chaachoo's theory by means of tf-idf analysis. A highorder n-gram model is applied to a corpus of 149 prescriptive transcriptions of heterophonic recordings, representing each as an unordered multiset of patterns. Computing the tf-idf statistic of each pattern in this corpus provides a means by which we can rank and compare motivic content across nawabāt, distinct musical forms of the tradition. For each nawba, an empirical comparison is made between patterns identified as significant via our approach and those proposed by Chaachoo. Ultimately we observe considerable agreement between the two pattern sets and go further in proposing new, unique and as yet undocumented patterns that occur at least as frequently and with at least as much importance as those in Chaachoo's proposals.\n
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\n \n\n \n \n \n \n \n \n Towards a Graphical User Interface for Quantitative Analysis in Digital Musicology.\n \n \n \n \n\n\n \n Ortloff, A.; Güntner, L.; and Schmidt, T.\n\n\n \n\n\n\n In Proc. Mensch und Computer 2019 - Workshopband, pages 535–538, Hamburg, Germany, 2019. Gesellschaft für Informatik e.V.\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    ortloff.ea2019-towards,\n    author       = {Ortloff, Anna-marie and G{\\"{u}}ntner, Lydia and Schmidt,\n                   Thomas},\n    year         = {2019},\n    title        = {Towards a Graphical User Interface for Quantitative\n                   Analysis in Digital Musicology},\n    abstract     = {computational musicology},\n    address      = {Hamburg, Germany},\n    booktitle    = {Proc. Mensch und Computer 2019 - Workshopband},\n    doi          = {10.18420/muc2019-ws-568},\n    keywords     = {Digital Musicology,Digital Musicology Statistical\n                   Musicology User Cen,Distant Hearing,Statistical\n                   Musicology,User Centered Design,Visualization},\n    mendeley-tags= {Digital Musicology Statistical Musicology User Cen},\n    pages        = {535--538},\n    publisher    = {Gesellschaft f{\\"{u}}r Informatik e.V.},\n    url          = {https://dl.gi.de/handle/20.500.12116/25202}\n}\n\n
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\n computational musicology\n
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\n \n\n \n \n \n \n \n \n Evolution of the Informational Complexity of Contemporary Western Music.\n \n \n \n \n\n\n \n Parmer, T.; and Ahn, Y.\n\n\n \n\n\n\n In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 175–182, Delft, The Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n \n \"EvolutionPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    parmer.ea2019-evolution,\n    author       = {Parmer, Thomas and Ahn, Yong-Yeol},\n    year         = {2019},\n    title        = {Evolution of the Informational Complexity of Contemporary\n                   Western Music},\n    abstract     = {We measure the complexity of songs in the Million Song\n                   Dataset (MSD) in terms of pitch, timbre, loudness, and\n                   rhythm to investigate their evolution from 1960 to 2010.\n                   By comparing the Billboard Hot 100 with random samples, we\n                   find that the complexity of popular songs tends to be more\n                   narrowly distributed around the mean, supporting the idea\n                   of an inverted U-shaped relationship between complexity\n                   and hedonistic value. We then examine the temporal\n                   evolution of complexity, reporting consistent changes\n                   across decades, such as a decrease in average loudness\n                   complexity since the 1960s, and an increase in timbre\n                   complexity overall but not for popular songs. We also\n                   show, in contrast to claims that popular songs sound more\n                   alike over time, that they are not more similar than they\n                   were 50 years ago in terms of pitch or rhythm, although\n                   similarity in timbre shows distinctive patterns across\n                   eras and similarity in loudness has been increasing.\n                   Finally, we show that musical genres can be differentiated\n                   by their distinctive complexity profiles.},\n    address      = {Delft, The Netherlands},\n    archiveprefix= {arXiv},\n    arxivid      = {1907.04292},\n    booktitle    = {Proceedings of the 20th International Society for Music\n                   Information Retrieval Conference},\n    doi          = {10.5281/zenodo.3527772},\n    eprint       = {1907.04292},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {175--182},\n    url          = {http://arxiv.org/abs/1907.04292}\n}\n\n
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\n\n\n
\n We measure the complexity of songs in the Million Song Dataset (MSD) in terms of pitch, timbre, loudness, and rhythm to investigate their evolution from 1960 to 2010. By comparing the Billboard Hot 100 with random samples, we find that the complexity of popular songs tends to be more narrowly distributed around the mean, supporting the idea of an inverted U-shaped relationship between complexity and hedonistic value. We then examine the temporal evolution of complexity, reporting consistent changes across decades, such as a decrease in average loudness complexity since the 1960s, and an increase in timbre complexity overall but not for popular songs. We also show, in contrast to claims that popular songs sound more alike over time, that they are not more similar than they were 50 years ago in terms of pitch or rhythm, although similarity in timbre shows distinctive patterns across eras and similarity in loudness has been increasing. Finally, we show that musical genres can be differentiated by their distinctive complexity profiles.\n
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\n\n\n
\n \n\n \n \n \n \n \n \n A convolutional approach to melody line identification in symbolic scores.\n \n \n \n \n\n\n \n Simonetta, F.; Cancino-chacón, C.; Widmer, G.; and Ntalampiras, S.\n\n\n \n\n\n\n Computing Research Repository, abs/1906.1. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          simonetta.ea2019-convolutional,\n    author       = {Simonetta, Federico and Cancino-chac{\\'{o}}n, Carlos and\n                   Widmer, Gerhard and Ntalampiras, Stavros},\n    year         = {2019},\n    title        = {A convolutional approach to melody line identification in\n                   symbolic scores},\n    archiveprefix= {arXiv},\n    arxivid      = {arXiv:1906.10547v1},\n    eprint       = {arXiv:1906.10547v1},\n    journal      = {Computing Research Repository},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    url          = {https://arxiv.org/pdf/1906.10547.pdf},\n    volume       = {abs/1906.1}\n}\n\n
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\n \n\n \n \n \n \n \n Composing with Textures : A Proposal for Formalization of Textural Spaces.\n \n \n \n\n\n \n de Sousa, D. M.\n\n\n \n\n\n\n MusMat - Brazilian Journal of Music and Mathematics, 3(1): 19–48. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          sousa2019-composing,\n    author       = {de Sousa, Daniel Moreira},\n    year         = {2019},\n    title        = {Composing with Textures : A Proposal for Formalization of\n                   Textural Spaces},\n    journal      = {MusMat - Brazilian Journal of Music and Mathematics},\n    keywords     = {music analysis,music composition,music theory,musical\n                   texture,textural spaces,theory of integer},\n    tags         = {music theory},\n    number       = {1},\n    pages        = {19--48},\n    volume       = {3}\n}\n\n
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\n \n\n \n \n \n \n \n Textural design: A Compositional Theory for the Organization of Musical Texture.\n \n \n \n\n\n \n de Sousa, D. M.\n\n\n \n\n\n\n Ph.D. Thesis, Universidade Federal do Rio de Janeiro, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@PhDThesis{        sousa2019-textural,\n    author       = {de Sousa, Daniel Moreira},\n    year         = {2019},\n    title        = {Textural design: A Compositional Theory for the\n                   Organization of Musical Texture},\n    keywords     = {Arrays,Compositional Designs,Musical Composition,Musical\n                   Texture,Pre compositional Strategy,music theory},\n    mendeley-tags= {music theory},\n    school       = {Universidade Federal do Rio de Janeiro},\n    type         = {Ph.D. Thesis}\n}\n\n
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\n \n\n \n \n \n \n \n \n Machine learning research that matters for music creation: A case study.\n \n \n \n \n\n\n \n Sturm, B. L.; Ben-Tal, O.; Monaghan, Ú.; Collins, N.; Herremans, D.; Chew, E.; Hadjeres, G.; Deruty, E.; and Pachet, F.\n\n\n \n\n\n\n Journal of New Music Research, 48(1): 36–55. jan 2019.\n \n\n\n\n
\n\n\n\n \n \n \"MachinePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          sturm.ea2019-machine,\n    author       = {Sturm, Bob L. and Ben-Tal, Oded and Monaghan, {\\'{U}}na\n                   and Collins, Nick and Herremans, Dorien and Chew, Elaine\n                   and Hadjeres, Ga{\\"{e}}tan and Deruty, Emmanuel and\n                   Pachet, Fran{\\c{c}}ois},\n    year         = {2019},\n    title        = {Machine learning research that matters for music\n                   creation: A case study},\n    abstract     = {Research applying machine learning to music modelling and\n                   generation typically proposes model architectures,\n                   training methods and datasets, and gauges system\n                   performance using quantitative measures like sequence\n                   likelihoods and/or qualitative listening tests. Rarely\n                   does such work explicitly question and analyse its\n                   usefulness for and impact on real-world practitioners, and\n                   then build on those outcomes to inform the development and\n                   application of machine learning. This article attempts to\n                   do these things for machine learning applied to music\n                   creation. Together with practitioners, we develop and use\n                   several applications of machine learning for music\n                   creation, and present a public concert of the results. We\n                   reflect on the entire experience to arrive at several ways\n                   of advancing these and similar applications of machine\n                   learning to music creation.},\n    doi          = {10.1080/09298215.2018.1515233},\n    issn         = {0929-8215},\n    journal      = {Journal of New Music Research},\n    keywords     = {Applied machine learning,computational creativity,folk\n                   music,music generation,music information retrieval},\n    mendeley-tags= {music information retrieval},\n    month        = {jan},\n    number       = {1},\n    pages        = {36--55},\n    url          = {https://www.tandfonline.com/doi/full/10.1080/09298215.2018.1515233},\n    volume       = {48}\n}\n\n
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\n Research applying machine learning to music modelling and generation typically proposes model architectures, training methods and datasets, and gauges system performance using quantitative measures like sequence likelihoods and/or qualitative listening tests. Rarely does such work explicitly question and analyse its usefulness for and impact on real-world practitioners, and then build on those outcomes to inform the development and application of machine learning. This article attempts to do these things for machine learning applied to music creation. Together with practitioners, we develop and use several applications of machine learning for music creation, and present a public concert of the results. We reflect on the entire experience to arrive at several ways of advancing these and similar applications of machine learning to music creation.\n
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\n \n\n \n \n \n \n \n \n Second-Position Syncopation in European and American Vocal Music.\n \n \n \n \n\n\n \n Temperley, D.\n\n\n \n\n\n\n Empirical Musicology Review, 14(1-2): 66. nov 2019.\n \n\n\n\n
\n\n\n\n \n \n \"Second-PositionPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          temperley2019-second-position,\n    author       = {Temperley, David},\n    year         = {2019},\n    title        = {Second-Position Syncopation in European and American\n                   Vocal Music},\n    abstract     = {I define a second-position syncopation as one involving a\n                   long note or accent on the second quarter of a half-note\n                   or quarter-note unit. I present a corpus analysis of\n                   second-position syncopation in 19th-century European and\n                   American vocal music. I argue that the analysis of\n                   syncopation requires consideration of other musical\n                   features besides note-onset patterns, including pitch\n                   contour, duration, and text-setting. The corpus analysis\n                   reveals that second-position syncopation was common in\n                   English, Scottish, Euro-American, and African-American\n                   vocal music, but rare in French, German, and Italian vocal\n                   music. This suggests that the prevalence of such\n                   syncopations in ragtime and later popular music was at\n                   least partly due to British influence.},\n    doi          = {10.18061/emr.v14i1-2.6986},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {19th-century scottish song,8th-note beat,a phrase from\n                   a,a short note on,a strong quarter-note beat,distinctive\n                   rhythmic,f igure 1a shows,first of all,followed by a\n                   longer,gesture,inside the box,it connects,music\n                   analysis,note on the following,of historical interest\n                   in,rhythm,scotch snap,several respects,syncopation,the\n                   phrase features a,this rhythmic pattern is,vocal\n                   music,with},\n    mendeley-tags= {music analysis},\n    month        = {nov},\n    number       = {1-2},\n    pages        = {66},\n    url          = {http://emusicology.org/article/view/6986},\n    volume       = {14}\n}\n\n
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\n I define a second-position syncopation as one involving a long note or accent on the second quarter of a half-note or quarter-note unit. I present a corpus analysis of second-position syncopation in 19th-century European and American vocal music. I argue that the analysis of syncopation requires consideration of other musical features besides note-onset patterns, including pitch contour, duration, and text-setting. The corpus analysis reveals that second-position syncopation was common in English, Scottish, Euro-American, and African-American vocal music, but rare in French, German, and Italian vocal music. This suggests that the prevalence of such syncopations in ragtime and later popular music was at least partly due to British influence.\n
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\n \n\n \n \n \n \n \n \n The RomanText Format: A Flexible and Standard Method for Representing Roman Numerial Analyses.\n \n \n \n \n\n\n \n Tymoczko, D.; Gotham, M.; Cuthbert, M.; and Ariza, C.\n\n\n \n\n\n\n In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 123–129, Delft, The Netherlands, 2019. \n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    tymoczko.ea2019-romantext,\n    author       = {Tymoczko, Dmitri and Gotham, Mark and Cuthbert, Michael\n                   and Ariza, Christopher},\n    year         = {2019},\n    title        = {The RomanText Format: A Flexible and Standard Method for\n                   Representing Roman Numerial Analyses},\n    address      = {Delft, The Netherlands},\n    booktitle    = {Proceedings of the 20th International Society for Music\n                   Information Retrieval Conference},\n    doi          = {10.5281/zenodo.3527756},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    pages        = {123--129},\n    url          = {https://zenodo.org/record/3527756#.XteB7Z7Yq9Z}\n}\n\n
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\n \n\n \n \n \n \n \n \n Tests of contrasting expressive content between first and second musical themes.\n \n \n \n \n\n\n \n Warrenburg, L. A; and Huron, D.\n\n\n \n\n\n\n Journal of New Music Research, 48(1): 21–35. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"TestsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          warrenburg.ea2019-tests,\n    author       = {Warrenburg, Lindsay A and Huron, David},\n    year         = {2019},\n    title        = {Tests of contrasting expressive content between first and\n                   second musical themes},\n    abstract     = {Since the eighteenth century, music theorists have noted\n                   the tendency for Western art-music works to contain themes\n                   exhibiting contrasting expressive content. In music\n                   exhibiting two main themes, the first theme is commonly\n                   characterised as ‘stronger' or ‘fiery', whereas the\n                   second theme tends to be ‘gentler' or ‘cantabile'. An\n                   examination of 1063 musical works indicates that second\n                   themes are less likely to be in the minor mode, but are\n                   more likely to be legato, slower in tempo, and involve a\n                   quieter dynamic level. Some observations are made\n                   regarding changes in the treatment of first and second\n                   themes over different stylistic periods.},\n    doi          = {10.1080/09298215.2018.1486435},\n    journal      = {Journal of New Music Research},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {1},\n    pages        = {21--35},\n    publisher    = {Routledge},\n    url          = {https://doi.org/10.1080/09298215.2018.1486435},\n    volume       = {48}\n}\n\n
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\n Since the eighteenth century, music theorists have noted the tendency for Western art-music works to contain themes exhibiting contrasting expressive content. In music exhibiting two main themes, the first theme is commonly characterised as ‘stronger' or ‘fiery', whereas the second theme tends to be ‘gentler' or ‘cantabile'. An examination of 1063 musical works indicates that second themes are less likely to be in the minor mode, but are more likely to be legato, slower in tempo, and involve a quieter dynamic level. Some observations are made regarding changes in the treatment of first and second themes over different stylistic periods.\n
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\n \n\n \n \n \n \n \n \n Distinguishing Chinese Guqin and Western Baroque pieces based on statistical model.\n \n \n \n \n\n\n \n Wu, Y.; and Li, S.\n\n\n \n\n\n\n In Proceedings of Computer Music Multidisciplinary Research 2019, pages 1–12, 2019. \n \n\n\n\n
\n\n\n\n \n \n \"DistinguishingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    wu.ea2019-distinguishing,\n    author       = {Wu, Yusong and Li, Shengchen},\n    year         = {2019},\n    title        = {Distinguishing Chinese Guqin and Western Baroque pieces\n                   based on statistical model},\n    booktitle    = {Proceedings of Computer Music Multidisciplinary Research\n                   2019},\n    keywords     = {computational musicology,machine learning,music\n                   similarity,statistics},\n    mendeley-tags= {music similarity},\n    pages        = {1--12},\n    url          = {https://lukewys.github.io/publications/CMMR2019}\n}\n\n
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\n \n\n \n \n \n \n \n \n Relevance of musical features for cadence detection.\n \n \n \n \n\n\n \n Bigo, L.; Feisthauer, L.; Giraud, M.; and Levé, F.\n\n\n \n\n\n\n In Proceedings of 19th International Conference on Music Information Retrieval, Paris, 2018. \n \n\n\n\n
\n\n\n\n \n \n \"RelevancePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    bigo.ea2018-relevance,\n    author       = {Bigo, Louis and Feisthauer, Laurent and Giraud, Mathieu\n                   and Lev{\\'{e}}, Florence},\n    year         = {2018},\n    title        = {Relevance of musical features for cadence detection},\n    abstract     = {Cadences, as breaths in music, are felt by the listener\n                   or studied by the theorist by combining harmony, melody,\n                   texture and possibly other musical aspects. We formalize\n                   and discuss the significance of 44 cadential features,\n                   correlated with the occurrence of cadences in scores.\n                   These features describe properties at the arrival beat of\n                   a cadence and its surroundings, but also at other onsets\n                   heuristically identified to pinpoint chords preparing the\n                   cadence. The representation of each beat of the score as a\n                   vector of cadential features makes it possible to\n                   reformulate cadence detection as a classification task. An\n                   SVM classifier was run on two corpora from Bach and Haydn\n                   totaling 162 perfect authentic cadences and 70 half\n                   cadences. In these corpora, the classifier correctly\n                   identified more than 75pct of perfect authentic cadences\n                   and 50pct of half cadences, with low false positive rates.\n                   The experiment results are consistent with common\n                   knowledge that classification is more complex for half\n                   cadences than for authentic cadences.},\n    address      = {Paris},\n    booktitle    = {Proceedings of 19th International Conference on Music\n                   Information Retrieval},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    url          = {https://hal.archives-ouvertes.fr/hal-01801060/}\n}\n\n
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\n Cadences, as breaths in music, are felt by the listener or studied by the theorist by combining harmony, melody, texture and possibly other musical aspects. We formalize and discuss the significance of 44 cadential features, correlated with the occurrence of cadences in scores. These features describe properties at the arrival beat of a cadence and its surroundings, but also at other onsets heuristically identified to pinpoint chords preparing the cadence. The representation of each beat of the score as a vector of cadential features makes it possible to reformulate cadence detection as a classification task. An SVM classifier was run on two corpora from Bach and Haydn totaling 162 perfect authentic cadences and 70 half cadences. In these corpora, the classifier correctly identified more than 75pct of perfect authentic cadences and 50pct of half cadences, with low false positive rates. The experiment results are consistent with common knowledge that classification is more complex for half cadences than for authentic cadences.\n
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\n \n\n \n \n \n \n \n \n An Exploratory Study of Western Orchestration: Patterns through History.\n \n \n \n \n\n\n \n Chon, S. H.; Huron, D.; and DeVlieger, D.\n\n\n \n\n\n\n Empirical Musicology Review, 12(3-4): 116. jun 2018.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          chon.ea2018-exploratory,\n    author       = {Chon, Song Hui and Huron, David and DeVlieger, Dana},\n    year         = {2018},\n    title        = {An Exploratory Study of Western Orchestration: Patterns\n                   through History},\n    abstract     = {Changes in instrument combination patterns in Western\n                   classical orchestral music are traced over a three hundred\n                   year period from 1701 to 2000. Using a stratified sample\n                   of sonorities from 180 orchestral works by 147 composers,\n                   various empirical analyses are reported. These include\n                   analyses of instrumentation presence, instrument usage,\n                   ensemble size, common instrument combinations, instrument\n                   clusterings, and their changes over time. In addition, the\n                   study reports associations of different instruments with\n                   various dynamic levels, different tempos, pitch class\n                   doublings, affinities between instruments and chord\n                   factors, as well as interactions between pitch, dynamics,\n                   and tempo. Results affirm many common intuitions and\n                   historical observations regarding orchestration, but also\n                   reveal a number of previously unrecognized patterns of\n                   instrument use.},\n    doi          = {10.18061/emr.v12i3-4.5773},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {1855,1885,1906,1914,1952,1964,berlioz,century,composers\n                   have written a,defined as the\n                   art,e,forsyth,g,gevaert,instrument\n                   combinations,instrumentation,kennan,music analysis with\n                   computers,music history,number of treatises on,o\n                   rchestration might be,of combining musical\n                   instruments,orchestration,rimsky-korsakov,since the mid-19\n                   th,sonorous effect,to produce a distinctive,widor},\n    mendeley-tags= {music analysis with computers},\n    month        = {jun},\n    number       = {3-4},\n    pages        = {116},\n    url          = {http://emusicology.org/article/view/5773},\n    volume       = {12}\n}\n\n
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\n Changes in instrument combination patterns in Western classical orchestral music are traced over a three hundred year period from 1701 to 2000. Using a stratified sample of sonorities from 180 orchestral works by 147 composers, various empirical analyses are reported. These include analyses of instrumentation presence, instrument usage, ensemble size, common instrument combinations, instrument clusterings, and their changes over time. In addition, the study reports associations of different instruments with various dynamic levels, different tempos, pitch class doublings, affinities between instruments and chord factors, as well as interactions between pitch, dynamics, and tempo. Results affirm many common intuitions and historical observations regarding orchestration, but also reveal a number of previously unrecognized patterns of instrument use.\n
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\n \n\n \n \n \n \n \n An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects.\n \n \n \n\n\n \n García-Vico, A. M.; Carmona, C. J.; Martín, D.; García-Borroto, M.; and del Jesus, M. J.\n\n\n \n\n\n\n Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(1): 1–22. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          garcia-vico.ea2018-overview,\n    author       = {Garc{\\'{i}}a-Vico, A. M. and Carmona, C. J. and\n                   Mart{\\'{i}}n, D. and Garc{\\'{i}}a-Borroto, M. and del\n                   Jesus, M. J.},\n    year         = {2018},\n    title        = {An overview of emerging pattern mining in supervised\n                   descriptive rule discovery: taxonomy, empirical study,\n                   trends, and prospects},\n    abstract     = {Emerging pattern mining is a data mining task that aims\n                   to discover discriminative patterns, which can describe\n                   emerging behavior with respect to a property of interest.\n                   In recent years, the description of datasets has become an\n                   interesting field due to the easy acquisition of knowledge\n                   by the experts. In this review, we will focus on the\n                   descriptive point of view of the task. We collect the\n                   existing approaches that have been proposed in the\n                   literature and group them together in a taxonomy in order\n                   to obtain a general vision of the task. A complete\n                   empirical study demonstrates the suitability of the\n                   approaches presented. This review also presents future\n                   trends and emerging prospects within pattern mining and\n                   the benefits of knowledge extracted from emerging\n                   patterns. WIREs Data Mining Knowl Discov 2018, 8:e1231.\n                   doi: 10.1002/widm.1231. This article is categorized under:\n                   Fundamental Concepts of Data and Knowledge > Knowledge\n                   Representation Fundamental Concepts of Data and Knowledge\n                   > Motivation and Emergence of Data Mining.},\n    doi          = {10.1002/widm.1231},\n    issn         = {19424795},\n    journal      = {Wiley Interdisciplinary Reviews: Data Mining and\n                   Knowledge Discovery},\n    keywords     = {computer},\n    mendeley-tags= {computer},\n    number       = {1},\n    pages        = {1--22},\n    volume       = {8}\n}\n\n
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\n Emerging pattern mining is a data mining task that aims to discover discriminative patterns, which can describe emerging behavior with respect to a property of interest. In recent years, the description of datasets has become an interesting field due to the easy acquisition of knowledge by the experts. In this review, we will focus on the descriptive point of view of the task. We collect the existing approaches that have been proposed in the literature and group them together in a taxonomy in order to obtain a general vision of the task. A complete empirical study demonstrates the suitability of the approaches presented. This review also presents future trends and emerging prospects within pattern mining and the benefits of knowledge extracted from emerging patterns. WIREs Data Mining Knowl Discov 2018, 8:e1231. doi: 10.1002/widm.1231. This article is categorized under: Fundamental Concepts of Data and Knowledge > Knowledge Representation Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining.\n
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\n \n\n \n \n \n \n \n \n Where Does Haydn End and Mozart Begin? Composer Classification of String Quartets.\n \n \n \n \n\n\n \n Kempfert, K. C.; and Wong, S. W. K.\n\n\n \n\n\n\n sep 2018.\n \n\n\n\n
\n\n\n\n \n \n \"WherePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@Misc{             kempfert.ea2018-where,\n    author       = {Kempfert, Katherine C. and Wong, Samuel W. K.},\n    year         = {2018},\n    title        = {Where Does Haydn End and Mozart Begin? Composer\n                   Classification of String Quartets},\n    abstract     = {For humans and machines, perceiving differences between\n                   string quartets by Joseph Haydn and Wolfgang Amadeus\n                   Mozart has been a challenging task, because of stylistic\n                   and compositional similarities between the composers.\n                   Based on the content of music scores, this study\n                   identifies and quantifies distinctions between these\n                   string quartets using statistical and machine learning\n                   techniques. Our approach develops new musically meaningful\n                   summary features based on the sonata form structure. Many\n                   of these proposed summary features are found to be\n                   important for distinguishing between Haydn and Mozart\n                   string quartets. Leave-one-out classification accuracy\n                   rates exceed 91\\%, significantly higher than has been\n                   attained for this task in prior work. These results\n                   indicate there are identifiable, musically insightful\n                   differences between string quartets by Haydn versus\n                   Mozart, such as in their low accompanying voices, Cello\n                   and Viola. Our quantitative approaches can expand the\n                   longstanding dialogue surrounding Haydn and Mozart,\n                   offering empirical evidence of claims made by\n                   musicologists. Our proposed framework, which interweaves\n                   musical scholarship with learning algorithms, can be\n                   applied to other composer classification tasks and\n                   quantitative studies of classical music in general.},\n    archiveprefix= {arXiv},\n    arxivid      = {1809.05075},\n    booktitle    = {arXiv},\n    eprint       = {1809.05075},\n    keywords     = {music analysis,music history},\n    mendeley-tags= {music analysis,music history},\n    month        = {sep},\n    pages        = {1--21},\n    url          = {http://arxiv.org/abs/1809.05075},\n    urldate      = {2018-09-13}\n}\n\n
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\n For humans and machines, perceiving differences between string quartets by Joseph Haydn and Wolfgang Amadeus Mozart has been a challenging task, because of stylistic and compositional similarities between the composers. Based on the content of music scores, this study identifies and quantifies distinctions between these string quartets using statistical and machine learning techniques. Our approach develops new musically meaningful summary features based on the sonata form structure. Many of these proposed summary features are found to be important for distinguishing between Haydn and Mozart string quartets. Leave-one-out classification accuracy rates exceed 91%, significantly higher than has been attained for this task in prior work. These results indicate there are identifiable, musically insightful differences between string quartets by Haydn versus Mozart, such as in their low accompanying voices, Cello and Viola. Our quantitative approaches can expand the longstanding dialogue surrounding Haydn and Mozart, offering empirical evidence of claims made by musicologists. Our proposed framework, which interweaves musical scholarship with learning algorithms, can be applied to other composer classification tasks and quantitative studies of classical music in general.\n
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\n \n\n \n \n \n \n \n X Section and Ethos in Sonata Forms by Haydn, Mozart, and early Beethoven.\n \n \n \n\n\n \n Libin, D. M\n\n\n \n\n\n\n Ph.D. Thesis, The State University of New Jersey, 2018.\n \n\n\n\n
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@PhDThesis{        libin2018-x,\n    author       = {Libin, Daniel M},\n    year         = {2018},\n    title        = {X Section and Ethos in Sonata Forms by Haydn, Mozart, and\n                   early Beethoven},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    school       = {The State University of New Jersey},\n    type         = {Ph.D. Thesis}\n}\n\n
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\n \n\n \n \n \n \n \n \n Another Look at Chromatic Third-Related Key Relationships in Late Haydn: Parallel Keys and Remote Modulation in Selected String Quartet Minuets.\n \n \n \n \n\n\n \n MacKay, J. S.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 2(3): 1–27. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"AnotherPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          mackay2018-another,\n    author       = {MacKay, James S.},\n    year         = {2018},\n    title        = {Another Look at Chromatic Third-Related Key Relationships\n                   in Late Haydn: Parallel Keys and Remote Modulation in\n                   Selected String Quartet Minuets},\n    abstract     = {As asserted by Ethan Haimo in a 1990 article, Joseph\n                   Haydn's Piano Trio in A-flat major, Hob. XV: 14 (1789-90),\n                   comprises his first use of a chromatic third relationship\n                   between movements of an instrumental work, with a I-flat\n                   VI-I tonal plan. This harmonic strategy, immediately taken\n                   up by Beethoven in his Piano Trio in G major, Op. 1 no. 2\n                   (slow movement in E, VI) and his Piano Sonata in C major,\n                   Op. 2 no. 3 (slow movement in E, III), quickly became a\n                   conventional feature of early 19 th-century tonality. Such\n                   third-related shifts in Haydn's instrumental music occur\n                   earlier than 1790, especially in his string quartet\n                   Minuet-Trio movements, often built around a parallel\n                   major-parallel minor pairing of keys and their relatives.\n                   For instance, in Haydn's String Quartet in F major, Op. 50\n                   no. 5 (Der Traum), third movement, Haydn effects a\n                   chromatic third modulation in two stages: touching briefly\n                   upon the parallel key (f minor) in the trio, then moving\n                   immediately to its relative major, A-flat (i.e. flat III\n                   of F major). As for works written after 1790, the Minuet\n                   and Trio of the Emperor Quartet in C major, Op. 76 no. 3,\n                   demonstrates the opposite strategy: after beginning the\n                   trio in the relative minor, Haydn shifts modally to its\n                   parallel key, A major, as the passage develops (VI of C\n                   major). As demonstrated by the above-mentioned quartet\n                   movements and others drawn from Opp. 74, 76, and 77, such\n                   two-stage chromatic third shifts at the formal level and\n                   this procedure's affinity with modal mixture, provides a\n                   new paradigm for understanding remote modulations, both in\n                   the late Classical period and beyond.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    number       = {3},\n    pages        = {1--27},\n    url          = {https://www.academia.edu/42811788/Another_Look_at_Chromatic_Third_Related_Key_Relationships_in_Late_Haydn_Parallel_Keys_and_Remote_Modulation_in_Selected_String_Quartet_Minuets?email_work_card=view-paper},\n    volume       = {2}\n}\n\n
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\n As asserted by Ethan Haimo in a 1990 article, Joseph Haydn's Piano Trio in A-flat major, Hob. XV: 14 (1789-90), comprises his first use of a chromatic third relationship between movements of an instrumental work, with a I-flat VI-I tonal plan. This harmonic strategy, immediately taken up by Beethoven in his Piano Trio in G major, Op. 1 no. 2 (slow movement in E, VI) and his Piano Sonata in C major, Op. 2 no. 3 (slow movement in E, III), quickly became a conventional feature of early 19 th-century tonality. Such third-related shifts in Haydn's instrumental music occur earlier than 1790, especially in his string quartet Minuet-Trio movements, often built around a parallel major-parallel minor pairing of keys and their relatives. For instance, in Haydn's String Quartet in F major, Op. 50 no. 5 (Der Traum), third movement, Haydn effects a chromatic third modulation in two stages: touching briefly upon the parallel key (f minor) in the trio, then moving immediately to its relative major, A-flat (i.e. flat III of F major). As for works written after 1790, the Minuet and Trio of the Emperor Quartet in C major, Op. 76 no. 3, demonstrates the opposite strategy: after beginning the trio in the relative minor, Haydn shifts modally to its parallel key, A major, as the passage develops (VI of C major). As demonstrated by the above-mentioned quartet movements and others drawn from Opp. 74, 76, and 77, such two-stage chromatic third shifts at the formal level and this procedure's affinity with modal mixture, provides a new paradigm for understanding remote modulations, both in the late Classical period and beyond.\n
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\n \n\n \n \n \n \n \n Interesting Haydn: On Attention's Materials.\n \n \n \n\n\n \n Mathew, N.\n\n\n \n\n\n\n Journal of the American Musicological Society, 71(3): 655–701. 2018.\n \n\n\n\n
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@Article{          mathew2018-interesting,\n    author       = {Mathew, Nicholas},\n    year         = {2018},\n    title        = {Interesting Haydn: On Attention's Materials},\n    doi          = {10.1525/jams.2018.71.3.655},\n    issn         = {0003-0139},\n    journal      = {Journal of the American Musicological Society},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    number       = {3},\n    pages        = {655--701},\n    volume       = {71}\n}\n\n
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\n \n\n \n \n \n \n \n \n The Annotated Beethoven Corpus (ABC): A Dataset of Harmonic Analyses of All Beethoven String Quartets.\n \n \n \n \n\n\n \n Neuwirth, M.; Harasim, D.; Moss, F. C.; and Rohrmeier, M.\n\n\n \n\n\n\n Frontiers in Digital Humanities, 5(July): 1–5. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          neuwirth.ea2018-annotated,\n    author       = {Neuwirth, Markus and Harasim, Daniel and Moss, Fabian\n                   Claude and Rohrmeier, Martin},\n    year         = {2018},\n    title        = {The Annotated Beethoven Corpus (ABC): A Dataset of\n                   Harmonic Analyses of All Beethoven String Quartets},\n    doi          = {10.3389/fdigh.2018.00016},\n    issn         = {2297-2668},\n    journal      = {Frontiers in Digital Humanities},\n    keywords     = {beethoven,corpus research,digital\n                   musicology,ground,ground truth,harmony,music,symbolic\n                   music data},\n    number       = {July},\n    pages        = {1--5},\n    url          = {https://www.frontiersin.org/article/10.3389/fdigh.2018.00016/full},\n    volume       = {5}\n}\n\n
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\n \n\n \n \n \n \n \n \n Contour Similarity Algorithms.\n \n \n \n \n\n\n \n Sampaio, M.\n\n\n \n\n\n\n MusMat - Brazilian Journal of Music and Mathematics, 2(2): 58–78. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"ContourPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          sampaio2018-contour,\n    author       = {{Sampaio}, {Marcos da Silva}},\n    year         = {2018},\n    title        = {Contour Similarity Algorithms},\n    abstract     = {The Musical Contour literature provides multiple\n                   algorithms for melodic contour similarity. However, most\n                   of them are limited in use by the melody length of input\n                   data. In this paper I review these algorithms, propose two\n                   new algorithms, compare them in three experiments with\n                   contours from the Bach Chorales, from a Schumann song and\n                   automated generated, and present a brief review of the\n                   contour and similarity literature.},\n    journal      = {MusMat - Brazilian Journal of Music and Mathematics},\n    keywords     = {Algorithms,Computational Musicology,Melodic\n                   Similarity,Music Analysis,Music Contour Theory,music\n                   contour},\n    mendeley-tags= {music contour},\n    number       = {2},\n    pages        = {58--78},\n    url          = {https://musmat.org/wp-content/uploads/2018/12/08-contour-similarity-algorithm.pdf},\n    volume       = {2}\n}\n\n
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\n The Musical Contour literature provides multiple algorithms for melodic contour similarity. However, most of them are limited in use by the melody length of input data. In this paper I review these algorithms, propose two new algorithms, compare them in three experiments with contours from the Bach Chorales, from a Schumann song and automated generated, and present a brief review of the contour and similarity literature.\n
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\n \n\n \n \n \n \n \n \n Simulating melodic and harmonic expectations for tonal cadences using probabilistic models.\n \n \n \n \n\n\n \n Sears, D. R.; Pearce, M. T.; Caplin, W. E.; and McAdams, S.\n\n\n \n\n\n\n Journal of New Music Research, 47(1): 29–52. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"SimulatingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          sears.ea2018-simulating,\n    author       = {Sears, David R.W. and Pearce, Marcus Thomas and Caplin,\n                   William Earl and McAdams, Stephen},\n    year         = {2018},\n    title        = {Simulating melodic and harmonic expectations for tonal\n                   cadences using probabilistic models},\n    abstract     = {This study examines how the mind's predictive mechanisms\n                   contribute to the perception of cadential closure during\n                   music listening. Using the Information Dynamics of Music\n                   model (or IDyOM) to simulate the formation of schematic\n                   expectations—a finite-context (or n-gram) model that\n                   predicts the next event in a musical stimulus by acquiring\n                   knowledge through unsupervised statistical learning of\n                   sequential structure—we predict the terminal melodic and\n                   harmonic events from 245 exemplars of the five most common\n                   cadence categories from the classical style. Our findings\n                   demonstrate that (1) terminal events from cadential\n                   contexts are more predictable than those from\n                   non-cadential contexts; (2) models of cadential strength\n                   advanced in contemporary cadence typologies reflect the\n                   formation of schematic expectations; and (3) a significant\n                   decrease in predictability follows the terminal note and\n                   chord events of the cadential formula.},\n    doi          = {10.1080/09298215.2017.1367010},\n    issn         = {17445027},\n    journal      = {Journal of New Music Research},\n    keywords     = {Cadence,expectation,music analysis with computers,n-gram\n                   models,segmental grouping,statistical learning},\n    mendeley-tags= {music analysis with computers},\n    number       = {1},\n    pages        = {29--52},\n    publisher    = {Routledge},\n    url          = {https://doi.org/10.1080/09298215.2017.1367010},\n    volume       = {47}\n}\n\n
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\n This study examines how the mind's predictive mechanisms contribute to the perception of cadential closure during music listening. Using the Information Dynamics of Music model (or IDyOM) to simulate the formation of schematic expectations—a finite-context (or n-gram) model that predicts the next event in a musical stimulus by acquiring knowledge through unsupervised statistical learning of sequential structure—we predict the terminal melodic and harmonic events from 245 exemplars of the five most common cadence categories from the classical style. Our findings demonstrate that (1) terminal events from cadential contexts are more predictable than those from non-cadential contexts; (2) models of cadential strength advanced in contemporary cadence typologies reflect the formation of schematic expectations; and (3) a significant decrease in predictability follows the terminal note and chord events of the cadential formula.\n
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\n \n\n \n \n \n \n \n \n Substantial musical similarity in sound and notation: Perspectives from digital musicology.\n \n \n \n \n\n\n \n Selfridge-Field, E.\n\n\n \n\n\n\n Colorado Technology Law Journal, 16(2): 249–284. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"SubstantialPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          selfridge-field2018-substantial,\n    author       = {Selfridge-Field, Eleanor},\n    year         = {2018},\n    title        = {Substantial musical similarity in sound and notation:\n                   Perspectives from digital musicology},\n    journal      = {Colorado Technology Law Journal},\n    keywords     = {music similarity},\n    mendeley-tags= {music similarity},\n    number       = {2},\n    pages        = {249--284},\n    url          = {https://heinonline.org/HOL/P?h=hein.journals/jtelhtel16&i=277},\n    volume       = {16}\n}\n\n
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\n \n\n \n \n \n \n \n \n Differentiae in the cantus manuscript database.\n \n \n \n \n\n\n \n Shaw, R.\n\n\n \n\n\n\n In Proceedings of the 5th International Conference on Digital Libraries for Musicology - DLfM '18, pages 38–46, New York, New York, USA, 2018. ACM Press\n \n\n\n\n
\n\n\n\n \n \n \"DifferentiaePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    shaw2018-differentiae,\n    author       = {Shaw, Rebecca},\n    year         = {2018},\n    title        = {Differentiae in the cantus manuscript database},\n    abstract     = {When approaching the study of medieval plainchant, one is\n                   inevitably confronted with its immensity, spanning several\n                   centuries and a wide geographic area. Even at a specific\n                   time and place, its notation and liturgy varies depending\n                   on the type of institution: local churches were influenced\n                   by the cathedral tradition, whilst monastic houses were\n                   influenced by local dioceses and their order, each of\n                   which regulated the liturgy to varying degrees. As such,\n                   each extant manuscript contains elements that could be\n                   regionally and/or globally standardized and/or not\n                   standardized, making large-scale data collection and\n                   analysis a daunting task. One method of tracing the\n                   relationships between manuscripts of different provenances\n                   is to examine a shared, stable feature, like differentiae\n                   in antiphoners. Differentiae, melodic formulas that set\n                   the final two words of the doxology, are always included\n                   at the end of psalm recitations in antiphonal psalmody and\n                   appear in conjunction with every antiphon in an\n                   antiphoner, regardless of the manuscript's provenance.\n                   This paper describes an ongoing project to standardize the\n                   differentiae field of the Cantus Manuscript Database so as\n                   to enable cross-manuscript comparisons. With over 1,400\n                   unique differentiae across 144 manuscripts (900s-1500s)\n                   processed to date, this project will enable scholars to\n                   explore hitherto unanswerable questions about not only the\n                   function of differentiae, but also, more broadly, chant\n                   transmission. To demonstrate the musicological potential\n                   of the differentiae standardization project, this paper\n                   includes a case study that interrogates the most commonly\n                   used definition of these melodic formulas: that they\n                   provided melodic transitions from psalm recitations to\n                   antiphon openings. The existence of this melodic\n                   connection is contested amongst scholars and its exact\n                   nature has never been clearly defined, due to the lack of\n                   available and standardized data. This paper demonstrates\n                   and defines the melodic relationship between differentiae\n                   and antiphon openings for the first of eight modes, whilst\n                   considering the ramifications of this relationship on the\n                   use of differentiae as mnemonic devices for the\n                   recollection of antiphon melodies.},\n    address      = {New York, New York, USA},\n    booktitle    = {Proceedings of the 5th International Conference on\n                   Digital Libraries for Musicology - DLfM '18},\n    doi          = {10.1145/3273024.3273028},\n    isbn         = {9781450365222},\n    keywords     = {Antiphonal psalmody,Antiphons,Differentia,Manuscript\n                   indices,Mnemonic\n                   devices,Mode,Plainchant,Standardization,computational\n                   musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {38--46},\n    publisher    = {ACM Press},\n    url          = {http://dl.acm.org/citation.cfm?doid=3273024.3273028}\n}\n\n
\n
\n\n\n
\n When approaching the study of medieval plainchant, one is inevitably confronted with its immensity, spanning several centuries and a wide geographic area. Even at a specific time and place, its notation and liturgy varies depending on the type of institution: local churches were influenced by the cathedral tradition, whilst monastic houses were influenced by local dioceses and their order, each of which regulated the liturgy to varying degrees. As such, each extant manuscript contains elements that could be regionally and/or globally standardized and/or not standardized, making large-scale data collection and analysis a daunting task. One method of tracing the relationships between manuscripts of different provenances is to examine a shared, stable feature, like differentiae in antiphoners. Differentiae, melodic formulas that set the final two words of the doxology, are always included at the end of psalm recitations in antiphonal psalmody and appear in conjunction with every antiphon in an antiphoner, regardless of the manuscript's provenance. This paper describes an ongoing project to standardize the differentiae field of the Cantus Manuscript Database so as to enable cross-manuscript comparisons. With over 1,400 unique differentiae across 144 manuscripts (900s-1500s) processed to date, this project will enable scholars to explore hitherto unanswerable questions about not only the function of differentiae, but also, more broadly, chant transmission. To demonstrate the musicological potential of the differentiae standardization project, this paper includes a case study that interrogates the most commonly used definition of these melodic formulas: that they provided melodic transitions from psalm recitations to antiphon openings. The existence of this melodic connection is contested amongst scholars and its exact nature has never been clearly defined, due to the lack of available and standardized data. This paper demonstrates and defines the melodic relationship between differentiae and antiphon openings for the first of eight modes, whilst considering the ramifications of this relationship on the use of differentiae as mnemonic devices for the recollection of antiphon melodies.\n
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\n \n\n \n \n \n \n \n Haydn's impropriety.\n \n \n \n\n\n \n Waltham-Smith, N.\n\n\n \n\n\n\n Journal of Music Theory, 62(1): 119–144. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          waltham-smith2018-haydns,\n    author       = {Waltham-Smith, Naomi},\n    year         = {2018},\n    title        = {Haydn's impropriety},\n    abstract     = {Haydn is known for his playful (mis)use of cadential\n                   formulas. Examining examples of this predilection and\n                   processes of cadential liquidation, this article develops\n                   a theory of the use of musical material. This entails a\n                   deconstruction of the Adornian dialectic between generic\n                   convention and particular expression and-following Jacques\n                   Derrida's notion of exappropriation-between proper and\n                   improper, and propriety and impropriety.},\n    doi          = {10.1215/00222909-4450660},\n    issn         = {00222909},\n    journal      = {Journal of Music Theory},\n    keywords     = {Cadence,Deconstruction,Exappropriation,Haydn,Liquidation,music\n                   analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {119--144},\n    volume       = {62}\n}\n\n
\n
\n\n\n
\n Haydn is known for his playful (mis)use of cadential formulas. Examining examples of this predilection and processes of cadential liquidation, this article develops a theory of the use of musical material. This entails a deconstruction of the Adornian dialectic between generic convention and particular expression and-following Jacques Derrida's notion of exappropriation-between proper and improper, and propriety and impropriety.\n
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\n \n\n \n \n \n \n \n \n Computational Corpus Analysis: a Case Study on Jazz Solos.\n \n \n \n \n\n\n \n Weiß, C.; Balke, S.; Abeßer, J.; and Müller, M.\n\n\n \n\n\n\n In Proceedings of the 19th International Society for Music Information Retrieval, Paris, 2018. \n \n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    wei.ea2018-computational,\n    author       = {Wei{\\ss}, Christof and Balke, Stefan and Abe{\\ss}er,\n                   Jakob and M{\\"{u}}ller, Meinard},\n    year         = {2018},\n    title        = {Computational Corpus Analysis: a Case Study on Jazz\n                   Solos},\n    abstract     = {For musicological studies on large corpora, the\n                   compilation of suitable data constitutes a time-consuming\n                   step. In particular, this is true for high-quality\n                   symbolic representations that are generated manually in a\n                   tedious process. A recent study on Western classical music\n                   has shown that musical phenomena such as the evolution of\n                   tonal complexity over history can also be analyzed on the\n                   basis of audio recordings. As our first contribution, we\n                   transfer this corpus analysis method to jazz music using\n                   the Weimar Jazz Database, which contains high-level\n                   symbolic transcriptions of jazz solos along with the audio\n                   recordings. Second, we investigate the influence of the\n                   input representation type on the corpus-level\n                   observations. In our experiments , all representation\n                   types led to qualitatively similar results. We conclude\n                   that audio recordings can build a reasonable basis for\n                   conducting such type of corpus analysis.},\n    address      = {Paris},\n    booktitle    = {Proceedings of the 19th International Society for Music\n                   Information Retrieval},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {October},\n    url          = {http://ismir2018.ircam.fr/doc/pdfs/23_Paper.pdf}\n}\n\n
\n
\n\n\n
\n For musicological studies on large corpora, the compilation of suitable data constitutes a time-consuming step. In particular, this is true for high-quality symbolic representations that are generated manually in a tedious process. A recent study on Western classical music has shown that musical phenomena such as the evolution of tonal complexity over history can also be analyzed on the basis of audio recordings. As our first contribution, we transfer this corpus analysis method to jazz music using the Weimar Jazz Database, which contains high-level symbolic transcriptions of jazz solos along with the audio recordings. Second, we investigate the influence of the input representation type on the corpus-level observations. In our experiments , all representation types led to qualitatively similar results. We conclude that audio recordings can build a reasonable basis for conducting such type of corpus analysis.\n
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\n \n\n \n \n \n \n \n \n Investigating style evolution of Western classical music: A computational approach.\n \n \n \n \n\n\n \n Weiß, C.; Mauch, M.; Dixon, S.; and Müller, M.\n\n\n \n\n\n\n Musicae Scientiae, (March). 2018.\n \n\n\n\n
\n\n\n\n \n \n \"InvestigatingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          wei.ea2018-investigating,\n    author       = {Wei{\\ss}, Christof and Mauch, Matthias and Dixon, Simon\n                   and M{\\"{u}}ller, Meinard},\n    year         = {2018},\n    title        = {Investigating style evolution of Western classical music:\n                   A computational approach},\n    abstract     = {In musicology, there has been a long debate about a\n                   meaningful partitioning and description of music history\n                   regarding composition styles. Particularly, concepts of\n                   historical periods have been criticized since they cannot\n                   account for the continuous and interwoven evolution of\n                   style. To systematically study this evolution, large\n                   corpora are necessary suggesting the use of computational\n                   strategies. This article presents such strategies and\n                   experiments relying on a dataset of 2000 audio recordings,\n                   which cover more than 300 years of music history. From the\n                   recordings, we extract different tonal features. We\n                   propose a method to visualize these features over the\n                   course of history using evolution curves. With the curves,\n                   we re-trace hypotheses concerning the evolution of chord\n                   transitions, intervals, and tonal complexity. Furthermore,\n                   we perform unsupervised clustering of recordings across\n                   composition years, individual pieces, and composers. In\n                   these studies, we found independent evidence of historical\n                   periods...},\n    doi          = {10.1177/1029864918757595},\n    isbn         = {1029864918},\n    issn         = {10298649},\n    journal      = {Musicae Scientiae},\n    keywords     = {composer style,computational musicology,corpus\n                   analysis,music analysis with computers,music information\n                   retrieval,style analysis,tonal audio features},\n    mendeley-tags= {music analysis with computers},\n    number       = {March},\n    url          = {https://www.researchgate.net/publication/323619682_Investigating_style_evolution_of_Western_classical_music_A_computational_approach}\n}\n\n
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\n In musicology, there has been a long debate about a meaningful partitioning and description of music history regarding composition styles. Particularly, concepts of historical periods have been criticized since they cannot account for the continuous and interwoven evolution of style. To systematically study this evolution, large corpora are necessary suggesting the use of computational strategies. This article presents such strategies and experiments relying on a dataset of 2000 audio recordings, which cover more than 300 years of music history. From the recordings, we extract different tonal features. We propose a method to visualize these features over the course of history using evolution curves. With the curves, we re-trace hypotheses concerning the evolution of chord transitions, intervals, and tonal complexity. Furthermore, we perform unsupervised clustering of recordings across composition years, individual pieces, and composers. In these studies, we found independent evidence of historical periods...\n
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\n  \n 2017\n \n \n (18)\n \n \n
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\n \n\n \n \n \n \n \n The digital music lab: A big data infrastructure for digital musicology.\n \n \n \n\n\n \n Abdallah, S.; Benetos, E.; Gold, N.; Hargreaves, S.; Weyde, T.; and Wolff, D.\n\n\n \n\n\n\n Journal on Computing and Cultural Heritage, 10(1): 1–21. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          abdallah.ea2017-digital,\n    author       = {Abdallah, Samer and Benetos, Emmanouil and Gold, Nicolas\n                   and Hargreaves, Steven and Weyde, Tillman and Wolff,\n                   Daniel},\n    year         = {2017},\n    title        = {The digital music lab: A big data infrastructure for\n                   digital musicology},\n    abstract     = {In musicology and music research generally, the\n                   increasing availability of digital music, storage\n                   capacities, and computing power enable and require new and\n                   intelligent systems. In the transition from traditional to\n                   digital musicology, many techniques and tools have been\n                   developed for the analysis of individual pieces of music,\n                   but large-scale music data that are increasingly becoming\n                   available require research methods and systems that work\n                   on the collection-level and at scale. Although many\n                   relevant algorithms have been developed during the past 15\n                   years of research in Music Information Retrieval, an\n                   integrated system that supports large-scale digital\n                   musicology research has so far been lacking. In the\n                   Digital Music Lab (DML) project, a collaboration among\n                   music librarians, musicologists, computer scientists, and\n                   human-computer interface specialists, the DML software\n                   system has been developed that fills this gap by providing\n                   intelligent large-scale music analysis with a\n                   user-friendly interactive interface supporting\n                   musicologists in their exploration and enquiry. The DML\n                   system empowers musicologists by addressing several\n                   challenges: distributed processing of audio and other\n                   music data, management of the data analysis process and\n                   results, remote analysis of data under copyright, logical\n                   inference on the extracted information and metadata, and\n                   visual web-based interfaces for exploring and querying the\n                   music collections. The DML system is scalable and based on\n                   SemanticWeb technology and integrates into Linked Data\n                   with the vision of a distributed system that enables music\n                   research across archives, libraries, and other providers\n                   of music data. A first DML system prototype has been set\n                   up in collaboration with the British Library and I Like\n                   Music Ltd. This system has been used to analyse a diverse\n                   corpus of currently 250,000 music tracks. In this article,\n                   we describe the DML system requirements, design,\n                   architecture, components, and available data sources,\n                   explaining their interaction. We report use cases and\n                   applications with initial evaluations of the proposed\n                   system.},\n    doi          = {10.1145/2983918},\n    issn         = {15564711},\n    journal      = {Journal on Computing and Cultural Heritage},\n    keywords     = {Big data,Digital musicology,Music information\n                   retrieval,Semantic web,computational musicology},\n    mendeley-tags= {computational musicology},\n    number       = {1},\n    pages        = {1--21},\n    volume       = {10}\n}\n\n
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\n In musicology and music research generally, the increasing availability of digital music, storage capacities, and computing power enable and require new and intelligent systems. In the transition from traditional to digital musicology, many techniques and tools have been developed for the analysis of individual pieces of music, but large-scale music data that are increasingly becoming available require research methods and systems that work on the collection-level and at scale. Although many relevant algorithms have been developed during the past 15 years of research in Music Information Retrieval, an integrated system that supports large-scale digital musicology research has so far been lacking. In the Digital Music Lab (DML) project, a collaboration among music librarians, musicologists, computer scientists, and human-computer interface specialists, the DML software system has been developed that fills this gap by providing intelligent large-scale music analysis with a user-friendly interactive interface supporting musicologists in their exploration and enquiry. The DML system empowers musicologists by addressing several challenges: distributed processing of audio and other music data, management of the data analysis process and results, remote analysis of data under copyright, logical inference on the extracted information and metadata, and visual web-based interfaces for exploring and querying the music collections. The DML system is scalable and based on SemanticWeb technology and integrates into Linked Data with the vision of a distributed system that enables music research across archives, libraries, and other providers of music data. A first DML system prototype has been set up in collaboration with the British Library and I Like Music Ltd. This system has been used to analyse a diverse corpus of currently 250,000 music tracks. In this article, we describe the DML system requirements, design, architecture, components, and available data sources, explaining their interaction. We report use cases and applications with initial evaluations of the proposed system.\n
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\n \n\n \n \n \n \n \n \n Sketching Sonata Form Structure in Selected Classical String Quartets.\n \n \n \n \n\n\n \n Bigo, L.; Giraud, M.; Groult, R.; Guiomard-Kagan, N.; and Levé, F.\n\n\n \n\n\n\n In Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR), pages 752–759, Suzhou, China, 2017. \n \n\n\n\n
\n\n\n\n \n \n \"SketchingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    bigo.ea2017-sketching,\n    author       = {Bigo, Louis and Giraud, Mathieu and Groult, Richard and\n                   Guiomard-Kagan, Nicolas and Lev{\\'{e}}, Florence},\n    year         = {2017},\n    title        = {Sketching Sonata Form Structure in Selected Classical\n                   String Quartets},\n    abstract     = {Many classical works from 18th and 19th centuries are\n                   sonata forms, exhibiting a piece-level tonal path through\n                   an exposition, a development and a recapitulation and\n                   in-volving two thematic zones as well as other elements.\n                   The computational music analysis of scores with such a\n                   large-scale structure is a challenge for the MIR community\n                   and should gather different analysis techniques. We\n                   propose first steps in that direction, combining analysis\n                   features on symbolic scores on patterns, harmony, and\n                   other elements into a structure estimated by a Viterbi\n                   algorithm on a Hid-den Markov Model. We test this strategy\n                   on a set of first movements of Haydn and Mozart string\n                   quartets. The pro-posed computational analysis strategy\n                   finds some pertinent features and sketches the sonata form\n                   structure in some pieces that have a simple sonata form.},\n    address      = {Suzhou, China},\n    booktitle    = {Proceedings of the 18th International Society for Music\n                   Information Retrieval Conference (ISMIR)},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {752--759},\n    url          = {https://ismir2017.smcnus.org/wp-content/uploads/2017/10/228_Paper.pdf}\n}\n\n
\n
\n\n\n
\n Many classical works from 18th and 19th centuries are sonata forms, exhibiting a piece-level tonal path through an exposition, a development and a recapitulation and in-volving two thematic zones as well as other elements. The computational music analysis of scores with such a large-scale structure is a challenge for the MIR community and should gather different analysis techniques. We propose first steps in that direction, combining analysis features on symbolic scores on patterns, harmony, and other elements into a structure estimated by a Viterbi algorithm on a Hid-den Markov Model. We test this strategy on a set of first movements of Haydn and Mozart string quartets. The pro-posed computational analysis strategy finds some pertinent features and sketches the sonata form structure in some pieces that have a simple sonata form.\n
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\n \n\n \n \n \n \n \n Practical Statistics for Data Scientists.\n \n \n \n\n\n \n Bruce, P.; and Bruce, A.\n\n\n \n\n\n\n O'Reilly Media, Sebastopol, CA, 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             bruce.ea2017-practical,\n    author       = {Bruce, Peter and Bruce, Andrew},\n    year         = {2017},\n    title        = {Practical Statistics for Data Scientists},\n    abstract     = {Statistical methods are a key part of of data science,\n                   yet very few data scientists have any formal statistics\n                   training. Courses and books on basic statistics rarely\n                   cover the topic from a data science perspective. This\n                   practical guide explains how to apply various statistical\n                   methods to data science, tells you how to avoid their\n                   misuse, and gives you advice on what's important and\n                   what's not. Many data science resources incorporate\n                   statistical methods but lack a deeper statistical\n                   perspective. If you're familiar with the R programming\n                   language, and have some exposure to statistics, this quick\n                   reference bridges the gap in an accessible, readable\n                   format.},\n    address      = {Sebastopol, CA},\n    isbn         = {9781491952894},\n    keywords     = {computer},\n    mendeley-tags= {computer},\n    publisher    = {O'Reilly Media}\n}\n\n
\n
\n\n\n
\n Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.\n
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\n \n\n \n \n \n \n \n PatternFinder: Content-Based Music Retrieval with music21.\n \n \n \n\n\n \n Garfinkle, D.; Arthur, C.; Schubert, P.; Cumming, J.; and Fujinaga, I.\n\n\n \n\n\n\n ACM International Conference Proceeding Series, (October): 5–8. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          garfinkle.ea2017-patternfinder,\n    author       = {Garfinkle, David and Arthur, Claire and Schubert, Peter\n                   and Cumming, Julie and Fujinaga, Ichiro},\n    year         = {2017},\n    title        = {PatternFinder: Content-Based Music Retrieval with\n                   music21},\n    abstract     = {Content-Based Music Retrieval (CBMR) for symbolic music\n                   aims to find all similar occurrences of a musical pattern\n                   within a larger database of symbolic music. To the best of\n                   our knowledge there does not currently exist a\n                   distributable CBMR software package integrated with a\n                   music analysis toolkit that facilitates extendability with\n                   new CBMR methods. This project presents a new MIR tool\n                   called "PatternFinder" satisfying these goals.\n                   PatternFinder is built with the computational musicology\n                   Python package music21, which provides a flexible platform\n                   capable of working with many music notation formats. To\n                   achieve polyphonic CBMR, we implement seven geometric\n                   algorithms developed at the University of Helsinki-four of\n                   which are being implemented and released publicly for the\n                   first time. The application of our MIR tool is then\n                   demonstrated through a musicological investigation of\n                   Renaissance imitation masses, which borrow melodic or\n                   contrapuntal material from a pre-existing musical work. In\n                   addition, we show Pattern-Finder's ability to find a\n                   contrapuntal pattern over a large dataset, Palestrina's\n                   104 masses. Our investigations demonstrate the relevance\n                   of our tool for musicological research as well as its\n                   potential application for locating music within digital\n                   music libraries.},\n    doi          = {10.1145/3144749.3144751},\n    isbn         = {9781450353472},\n    journal      = {ACM International Conference Proceeding Series},\n    keywords     = {Content-based music retrieval,Imitation\n                   masses,Music21,Point-set similarity,Polyphonic\n                   search,Symbolic music\n                   similarity,Time-scaled,Time-warped,Transpositioninvariant,music\n                   information retrieval},\n    mendeley-tags= {music information retrieval},\n    number       = {October},\n    pages        = {5--8}\n}\n\n
\n
\n\n\n
\n Content-Based Music Retrieval (CBMR) for symbolic music aims to find all similar occurrences of a musical pattern within a larger database of symbolic music. To the best of our knowledge there does not currently exist a distributable CBMR software package integrated with a music analysis toolkit that facilitates extendability with new CBMR methods. This project presents a new MIR tool called \"PatternFinder\" satisfying these goals. PatternFinder is built with the computational musicology Python package music21, which provides a flexible platform capable of working with many music notation formats. To achieve polyphonic CBMR, we implement seven geometric algorithms developed at the University of Helsinki-four of which are being implemented and released publicly for the first time. The application of our MIR tool is then demonstrated through a musicological investigation of Renaissance imitation masses, which borrow melodic or contrapuntal material from a pre-existing musical work. In addition, we show Pattern-Finder's ability to find a contrapuntal pattern over a large dataset, Palestrina's 104 masses. Our investigations demonstrate the relevance of our tool for musicological research as well as its potential application for locating music within digital music libraries.\n
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\n \n\n \n \n \n \n \n \n Nestings and Intersections between Partitional Complexes.\n \n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n MusMat - Brazilian Journal of Music and Mathematics, I(2): 93–108. 2017.\n \n\n\n\n
\n\n\n\n \n \n \"NestingsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          gentil-nunes2017-nestings,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2017},\n    title        = {Nestings and {Intersections} between {Partitional}\n                   {Complexes}},\n    volume       = {I},\n    url          = {https://musmat.org/wp-content/uploads/2018/06/09-Pauxy.pdf},\n    abstract     = {The formalization of musical texture is the main\n                   objective of Partitional Analysis. Each integer partition\n                   corresponds to a specific textural configuration and is\n                   used as a tool to organize and systematize the work with\n                   textures through the compositional process. Partitional\n                   complexes, on the other hand, are sets of partitions,\n                   observed in the analysis of musical excerpts, that work in\n                   tune to create stable temporal domains where a referential\n                   partition projects, extends or presents itself as\n                   dominant. The number of partitions and complexes for a\n                   certain instrumental, vocal or electronic medium is finite\n                   and implies nestings and intersections that can provide\n                   important information about textural possibilities\n                   available to the composer. In the present work, the\n                   relationships establishedbetween distinct partitional\n                   complexes are discussed, as well as the characterization\n                   of an hierarchy related to the number of total choices\n                   that each complex offers to the composer.},\n    language     = {English},\n    number       = {2},\n    journal      = {MusMat - Brazilian Journal of Music and Mathematics},\n    keywords     = {Rhythmic partitioning},\n    pages        = {93--108}\n}\n\n
\n
\n\n\n
\n The formalization of musical texture is the main objective of Partitional Analysis. Each integer partition corresponds to a specific textural configuration and is used as a tool to organize and systematize the work with textures through the compositional process. Partitional complexes, on the other hand, are sets of partitions, observed in the analysis of musical excerpts, that work in tune to create stable temporal domains where a referential partition projects, extends or presents itself as dominant. The number of partitions and complexes for a certain instrumental, vocal or electronic medium is finite and implies nestings and intersections that can provide important information about textural possibilities available to the composer. In the present work, the relationships establishedbetween distinct partitional complexes are discussed, as well as the characterization of an hierarchy related to the number of total choices that each complex offers to the composer.\n
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\n \n\n \n \n \n \n \n 12.\n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n Partitiogram, Mnet, Vnet and Tnet: Embedded Abstractions Inside Compositional Games, pages 111–118. Springer, Berlin, 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InBook{           gentil-nunes2017-partitiogram,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2017},\n    title        = {Partitiogram, Mnet, Vnet and Tnet: Embedded Abstractions\n                   Inside Compositional Games},\n    chapter      = {12},\n    pages        = {111--118},\n    address      = {Berlin},\n    publisher    = {Springer},\n    booktitle    = {The Musical-Mathematical Mind: Patterns and\n                   Transformations}\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Teorias analíticas sobre a textura musical no Brasil.\n \n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n In Nogueira, I., editor(s), Teoria e Análise Musical em Perspectiva Didática, 9, pages 139–151. TeMA, Salvador, 2017.\n \n\n\n\n
\n\n\n\n \n \n \"TeoriasPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     gentil-nunes2017-teorias,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2017},\n    title        = {Teorias anal\\'{i}ticas sobre a textura musical no Brasil},\n    address      = {Salvador},\n    booktitle    = {Teoria e An\\'{a}lise Musical em Perspectiva Did\\'{a}tica},\n    chapter      = {9},\n    editor       = {Nogueira, Ilza},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    pages        = {139--151},\n    publisher    = {TeMA},\n    url          = {https://tema.mus.br/novo/series.html}\n}\n\n
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\n \n\n \n \n \n \n \n \n Western classical music development: a statistical analysis of composers similarity, differentiation and evolution.\n \n \n \n \n\n\n \n Georges, P.\n\n\n \n\n\n\n Scientometrics, 112(1): 21–53. jul 2017.\n \n\n\n\n
\n\n\n\n \n \n \"WesternPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          georges2017-western,\n    author       = {Georges, Patrick},\n    year         = {2017},\n    title        = {Western classical music development: a statistical\n                   analysis of composers similarity, differentiation and\n                   evolution},\n    abstract     = {This paper proposes a statistical analysis that captures\n                   similarities and differences between classical music\n                   composers with the eventual aim to understand why\n                   particular composers 'sound' different even if their\n                   'lineages' (influences network) are similar or why they\n                   'sound' alike if their 'lineages' are different. In order\n                   to do this we use statistical methods and measures of\n                   association or similarity (based on presence/absence of\n                   traits such as specific 'ecological' characteristics and\n                   personal musical influences) that have been developed in\n                   biosystematics, scientometrics, and bibliographic\n                   coupling. This paper also represents a first step towards\n                   a more ambitious goal of developing an evolutionary model\n                   of Western classical music.},\n    doi          = {10.1007/s11192-017-2387-x},\n    issn         = {0138-9130},\n    journal      = {Scientometrics},\n    keywords     = {Classical\n                   composers,Differentiation,Evolution,Imitation,Influences\n                   network,Similarity indices,music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    month        = {jul},\n    number       = {1},\n    pages        = {21--53},\n    url          = {http://link.springer.com/10.1007/s11192-017-2387-x},\n    volume       = {112}\n}\n\n
\n
\n\n\n
\n This paper proposes a statistical analysis that captures similarities and differences between classical music composers with the eventual aim to understand why particular composers 'sound' different even if their 'lineages' (influences network) are similar or why they 'sound' alike if their 'lineages' are different. In order to do this we use statistical methods and measures of association or similarity (based on presence/absence of traits such as specific 'ecological' characteristics and personal musical influences) that have been developed in biosystematics, scientometrics, and bibliographic coupling. This paper also represents a first step towards a more ambitious goal of developing an evolutionary model of Western classical music.\n
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\n \n\n \n \n \n \n \n Of beginnings and ends a corpus-based inquiry into the rise of the recapitulation.\n \n \n \n\n\n \n Greenberg, Y.\n\n\n \n\n\n\n Journal of Music Theory, 61(2): 171–200. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          greenberg2017-beginnings,\n    author       = {Greenberg, Yoel},\n    year         = {2017},\n    title        = {Of beginnings and ends a corpus-based inquiry into the\n                   rise of the recapitulation},\n    abstract     = {This article investigates the sources of the\n                   recapitulation using statistical methods. The\n                   recapitulation has traditionally been viewed as an\n                   expansion of small ternary forms, resulting in a top-down\n                   approach, whereby the repeat of expositional material is\n                   explained in rotational terms. Here I present a bottom-up\n                   approach, demonstrating that the recapitulation arose as a\n                   concatenation between two previously independent\n                   practices: the double return of the opening theme in the\n                   tonic in the middle of the second half of a two-part form,\n                   and the thematic matching between the ends of the two\n                   halves of two-part form. Drawing on a corpus of more than\n                   seven hundred instrumental works dated 1650-1770, I\n                   demonstrate that these two practices arose and functioned\n                   independently from each other, increasing in frequency and\n                   in length, before being subsumed into an overarching\n                   rotational practice.},\n    doi          = {10.1215/00222909-4149546},\n    issn         = {00222909},\n    journal      = {Journal of Music Theory},\n    keywords     = {Big data,Double return,End-rhyme,Recapitulation,Sonata\n                   form,music theory},\n    mendeley-tags= {music theory},\n    number       = {2},\n    pages        = {171--200},\n    volume       = {61}\n}\n\n
\n
\n\n\n
\n This article investigates the sources of the recapitulation using statistical methods. The recapitulation has traditionally been viewed as an expansion of small ternary forms, resulting in a top-down approach, whereby the repeat of expositional material is explained in rotational terms. Here I present a bottom-up approach, demonstrating that the recapitulation arose as a concatenation between two previously independent practices: the double return of the opening theme in the tonic in the middle of the second half of a two-part form, and the thematic matching between the ends of the two halves of two-part form. Drawing on a corpus of more than seven hundred instrumental works dated 1650-1770, I demonstrate that these two practices arose and functioned independently from each other, increasing in frequency and in length, before being subsumed into an overarching rotational practice.\n
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\n \n\n \n \n \n \n \n Trimodular Block Strategies in Haydn's Sonata Movements by Samantha M. Inman.\n \n \n \n\n\n \n Inman, S. M.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 7(Spring): 1–27. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          inman2017-trimodular,\n    author       = {Inman, Samantha M.},\n    year         = {2017},\n    title        = {Trimodular Block Strategies in Haydn's Sonata Movements\n                   by Samantha M. Inman},\n    abstract     = {This study combines concepts from Hepokoski and Darcy,\n                   and Caplin, to examine Haydn's approaches to the\n                   trimodular block (TMB). The first part of the article\n                   proposes three categories of TMBs based on which modules\n                   of a given TMB lie within S and the stability of the\n                   opening of TM3. Subsequent parts use these three\n                   categories to identify patterns in Haydn's instrumental\n                   movements containing TMBs. Data regarding the fundamental\n                   features of forty-one movements are combined with in-depth\n                   analyses of three representative movements, one for each\n                   TMB category. While some traits remain consistent across\n                   all three categories, other traits typical of a single\n                   category in Haydn's output correlate with specific\n                   recapitulatory strategies.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {Spring},\n    pages        = {1--27},\n    volume       = {7}\n}\n\n
\n
\n\n\n
\n This study combines concepts from Hepokoski and Darcy, and Caplin, to examine Haydn's approaches to the trimodular block (TMB). The first part of the article proposes three categories of TMBs based on which modules of a given TMB lie within S and the stability of the opening of TM3. Subsequent parts use these three categories to identify patterns in Haydn's instrumental movements containing TMBs. Data regarding the fundamental features of forty-one movements are combined with in-depth analyses of three representative movements, one for each TMB category. While some traits remain consistent across all three categories, other traits typical of a single category in Haydn's output correlate with specific recapitulatory strategies.\n
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\n \n\n \n \n \n \n \n \n Finding Occurrences of Melodic Segments in Folk Songs Employing Symbolic Similarity Measures.\n \n \n \n \n\n\n \n Janssen, B.; van Kranenburg, P.; and Volk, A.\n\n\n \n\n\n\n Journal of New Music Research, 46(2): 118–134. apr 2017.\n \n\n\n\n
\n\n\n\n \n \n \"FindingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          janssen.ea2017-finding,\n    author       = {Janssen, Berit and van Kranenburg, Peter and Volk, Anja},\n    year         = {2017},\n    title        = {Finding Occurrences of Melodic Segments in Folk Songs\n                   Employing Symbolic Similarity Measures},\n    abstract     = {Much research has been devoted to the classification of\n                   folk songs, revealing that variants are recognised based\n                   on salient melodic segments, such as phrases and motifs,\n                   while other musical material in a melody might vary\n                   considerably. In order to judge similarity of melodies on\n                   the level of melodic segments, a successful similarity\n                   measure is needed which will allow finding occurrences of\n                   melodic segments in folk songs reliably. The present study\n                   compares several such similarity measures from different\n                   music research domains: correlation distance, city block\n                   distance, Euclidean distance, local align-ment, wavelet\n                   transform and structure induction. We evaluate the\n                   measures against annotations of phrase occurrences in a\n                   corpus of Dutch folk songs, observing whether the\n                   mea-sures detect annotated occurrences at the correct\n                   positions. Moreover, we investigate the influence of music\n                   represen-tation on the success of the various measures,\n                   and analyse the robustness of the most successful measures\n                   over subsets of the data. Our results reveal that\n                   structure induction is a promising approach, but that\n                   local alignment and city block distance perform even\n                   better when applied to adjusted music representations.\n                   These three methods can be combined to find occurrences\n                   with increased precision.},\n    doi          = {10.1080/09298215.2017.1316292},\n    issn         = {0929-8215},\n    journal      = {Journal of New Music Research},\n    keywords     = {music analysis with computers,music\n                   similarity,occurrences,pattern\n                   matching,segments,symbolic},\n    mendeley-tags= {music analysis with computers},\n    month        = {apr},\n    number       = {2},\n    pages        = {118--134},\n    url          = {https://www.tandfonline.com/doi/full/10.1080/09298215.2017.1316292},\n    volume       = {46}\n}\n\n
\n
\n\n\n
\n Much research has been devoted to the classification of folk songs, revealing that variants are recognised based on salient melodic segments, such as phrases and motifs, while other musical material in a melody might vary considerably. In order to judge similarity of melodies on the level of melodic segments, a successful similarity measure is needed which will allow finding occurrences of melodic segments in folk songs reliably. The present study compares several such similarity measures from different music research domains: correlation distance, city block distance, Euclidean distance, local align-ment, wavelet transform and structure induction. We evaluate the measures against annotations of phrase occurrences in a corpus of Dutch folk songs, observing whether the mea-sures detect annotated occurrences at the correct positions. Moreover, we investigate the influence of music represen-tation on the success of the various measures, and analyse the robustness of the most successful measures over subsets of the data. Our results reveal that structure induction is a promising approach, but that local alignment and city block distance perform even better when applied to adjusted music representations. These three methods can be combined to find occurrences with increased precision.\n
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\n \n\n \n \n \n \n \n Tonal Harmony: with an Introduction to Post-Tonal Music.\n \n \n \n\n\n \n Kostka, S. M.; Payne, D.; and Almén, B.\n\n\n \n\n\n\n McGraw-Hill Education, New York, 8 edition, 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             kostka.ea2017-tonal,\n    author       = {Kostka, Stefan M. and Payne, Dorothy and Alm{\\'{e}}n,\n                   Byron},\n    year         = {2017},\n    title        = {Tonal Harmony: with an Introduction to Post-Tonal Music},\n    address      = {New York},\n    edition      = {8},\n    isbn         = {9788578110796},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {McGraw-Hill Education}\n}\n\n
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\n \n\n \n \n \n \n \n Documenting a song culture: the Dutch Song Database as a resource for musicological research.\n \n \n \n\n\n \n van Kranenburg, P.; de Bruin, M.; and Volk, A.\n\n\n \n\n\n\n International Journal on Digital Libraries, 20(1): 13–23. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          kranenburg.ea2017-documenting,\n    author       = {van Kranenburg, Peter and de Bruin, Martine and Volk,\n                   Anja},\n    year         = {2017},\n    title        = {Documenting a song culture: the Dutch Song Database as a\n                   resource for musicological research},\n    abstract     = {The Dutch Song Database is a digital repository\n                   documenting Dutch song culture in past and present. It\n                   contains more than 173 thousand references to song\n                   occurrences in the Dutch and Flemish language, from the\n                   Middle Ages up to the present, as well as over 18 thousand\n                   descriptions of song sources, such as song books,\n                   manuscripts and field recordings, all adhering to high\n                   quality standards. In this paper, we present the history\n                   and functionality of the database, and we demonstrate how\n                   the Dutch Song Database facilitates and enables\n                   musicological research by presenting its contents and\n                   search functionalities in a number of exemplary cases. We\n                   discuss difficulties and impediments that were encountered\n                   during the development of the database, and we sketch a\n                   future prospect for further development in the European\n                   context.},\n    doi          = {10.1007/s00799-017-0228-4},\n    issn         = {14321300},\n    journal      = {International Journal on Digital Libraries},\n    keywords     = {Database,Dutch song culture,History,Information\n                   retrieval,Literature,Metadata,Musicology,computational\n                   musicology},\n    mendeley-tags= {computational musicology},\n    number       = {1},\n    pages        = {13--23},\n    publisher    = {Springer Berlin Heidelberg},\n    volume       = {20}\n}\n\n
\n
\n\n\n
\n The Dutch Song Database is a digital repository documenting Dutch song culture in past and present. It contains more than 173 thousand references to song occurrences in the Dutch and Flemish language, from the Middle Ages up to the present, as well as over 18 thousand descriptions of song sources, such as song books, manuscripts and field recordings, all adhering to high quality standards. In this paper, we present the history and functionality of the database, and we demonstrate how the Dutch Song Database facilitates and enables musicological research by presenting its contents and search functionalities in a number of exemplary cases. We discuss difficulties and impediments that were encountered during the development of the database, and we sketch a future prospect for further development in the European context.\n
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\n \n\n \n \n \n \n \n A Case for Declassifying the IAC as a Cadence Type: Cadence and Thematic Design in Selected Early- to Middle-Period Haydn Sonatas.\n \n \n \n\n\n \n MacKay, J. S.\n\n\n \n\n\n\n Ad Parnassum, 15(30): 1–27. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          mackay2017-case,\n    author       = {MacKay, James S.},\n    year         = {2017},\n    title        = {A Case for Declassifying the IAC as a Cadence Type:\n                   Cadence and Thematic Design in Selected Early- to\n                   Middle-Period Haydn Sonatas},\n    journal      = {Ad Parnassum},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {30},\n    pages        = {1--27},\n    volume       = {15}\n}\n\n
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\n \n\n \n \n \n \n \n \n Practical Time Series Analysis: Master Time Series Data Processing, Visualization, and Modeling using Python.\n \n \n \n \n\n\n \n Pal, A.; and Prakash, P.\n\n\n \n\n\n\n Packt Publishing, Birmingham; Mumbai, 2017.\n \n\n\n\n
\n\n\n\n \n \n \"PracticalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             pal.ea2017-practical,\n    author       = {Pal, Avishek and Prakash, PKS},\n    year         = {2017},\n    title        = {Practical Time Series Analysis: Master Time Series Data\n                   Processing, Visualization, and Modeling using Python},\n    address      = {Birmingham; Mumbai},\n    booktitle    = {Packt Publishing},\n    isbn         = {9781788290227},\n    keywords     = {statistics},\n    mendeley-tags= {statistics},\n    publisher    = {Packt Publishing},\n    url          = {https://www.packtpub.com/big-data-and-business-intelligence/practical-time-series-analysis}\n}\n\n
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\n \n\n \n \n \n \n \n A computational study on outliers in world music.\n \n \n \n\n\n \n Panteli, M.; Benetos, E.; and Dixon, S.\n\n\n \n\n\n\n PLoS ONE, 12(12): 1–29. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          panteli.ea2017-computational,\n    author       = {Panteli, Maria and Benetos, Emmanouil and Dixon, Simon},\n    year         = {2017},\n    title        = {A computational study on outliers in world music},\n    abstract     = {The comparative analysis of world music cultures has been\n                   the focus of several ethnomusicological studies in the\n                   last century. With the advances of Music Information\n                   Retrieval and the increased accessibility of sound\n                   archives, large-scale analysis of world music with\n                   computational tools is today feasible. We investigate\n                   music similarity in a corpus of 8200 recordings of folk\n                   and traditional music from 137 countries around the world.\n                   In particular, we aim to identify music recordings that\n                   are most distinct compared to the rest of our corpus. We\n                   refer to these recordings as ‘outliers'. We use signal\n                   processing tools to extract music information from audio\n                   recordings, data mining to quantify similarity and detect\n                   outliers, and spatial statistics to account for\n                   geographical correlation. Our findings suggest that\n                   Botswana is the country with the most distinct recordings\n                   in the corpus and China is the country with the most\n                   distinct recordings when considering spatial correlation.\n                   Our analysis includes a comparison of musical attributes\n                   and styles that contribute to the ‘uniqueness' of the\n                   music of each country.},\n    doi          = {10.1371/journal.pone.0189399},\n    isbn         = {1111111111},\n    issn         = {19326203},\n    journal      = {PLoS ONE},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    number       = {12},\n    pages        = {1--29},\n    pmid         = {29253027},\n    volume       = {12}\n}\n\n
\n
\n\n\n
\n The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers'. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness' of the music of each country.\n
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\n \n\n \n \n \n \n \n A Teoria de Relações de Contornos no Brasil.\n \n \n \n\n\n \n Sampaio, M.\n\n\n \n\n\n\n In Nogueira, I., editor(s), Teoria e Análise Musical em perspectiva didática, 8, pages 123–138. EDUFBA, Salvador, BA, 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     sampaio2017-teoria,\n    author       = {{Sampaio}, {Marcos da Silva}},\n    year         = {2017},\n    title        = {A Teoria de Rela{\\c{c}}{\\~{o}}es de Contornos no Brasil},\n    abstract     = {The Theory of Musical Contours was initially developed by\n                   Robert Morris, Elizabeth Marvin and Michael Friedmann as a\n                   support for the study of musical contours. Since the\n                   1980s, dozens of authors have used it as a basis for their\n                   studies. In Brazil, this theory has been used both as a\n                   support for Analysis and for Musical Composition. In this\n                   work we present the approaches, applications of this\n                   theory in studies carried out in Brazil and its\n                   peculiarities. We identified the role of postgraduate\n                   students in the use of this theory and the tendency to\n                   apply it in the area of Musical Composition.},\n    address      = {Salvador, BA},\n    booktitle    = {Teoria e An{\\'{a}}lise Musical em perspectiva\n                   did{\\'{a}}tica},\n    chapter      = {8},\n    editor       = {Nogueira, Ilza},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    pages        = {123--138},\n    publisher    = {EDUFBA}\n}\n\n
\n
\n\n\n
\n The Theory of Musical Contours was initially developed by Robert Morris, Elizabeth Marvin and Michael Friedmann as a support for the study of musical contours. Since the 1980s, dozens of authors have used it as a basis for their studies. In Brazil, this theory has been used both as a support for Analysis and for Musical Composition. In this work we present the approaches, applications of this theory in studies carried out in Brazil and its peculiarities. We identified the role of postgraduate students in the use of this theory and the tendency to apply it in the area of Musical Composition.\n
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\n \n\n \n \n \n \n \n \n Pasts and futures of digital humanities in musicology: Moving towards a “Bigger Tent”.\n \n \n \n \n\n\n \n Urberg, M.\n\n\n \n\n\n\n Music Reference Services Quarterly, 20(3-4): 134–150. 2017.\n \n\n\n\n
\n\n\n\n \n \n \"PastsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          urberg2017-pasts,\n    author       = {Urberg, Michelle},\n    year         = {2017},\n    title        = {Pasts and futures of digital humanities in musicology:\n                   Moving towards a “Bigger Tent”},\n    abstract     = {Musicologists and music theorists have traditionally been\n                   early adopters of technological tools to assist with\n                   research. The earliest digital humanities projects in\n                   musicology and music theory came directly out of\n                   humanities computing and quantitative analytical\n                   technologies developed in the 1980s, but newer projects\n                   created since the mid-2000s still reflect this past of\n                   algorithmic analysis and archival compilation, retrieval,\n                   and display. Computational and archival research is,\n                   currently, only one branch of digital humanities. The\n                   umbrella of digital humanities research now also includes\n                   digital publishing, philosophies of digital research, and\n                   “born digital” projects that cannot exist outside of a\n                   digital medium (e.g., virtual reality or 3D modeling).\n                   This shift in the digital humanities represents a move to\n                   a “bigger tent” that includes more types of projects.\n                   Musicological and musico-theoretical scholarship is slowly\n                   moving in this direction. Music librarians have been at\n                   the forefront of identifying and promoting new digital\n                   tools and archives, even though these projects have tended\n                   to remain at the periphery of musico-theoretical\n                   discourse. They should be on the lookout for “bigger\n                   tent” projects, such as medieval and renaissance\n                   projects like the Isabelle D'Este Archive, Opening the\n                   Geesebook, and the Experience of Worship. These projects\n                   are characterized by being iterative and multi-modally\n                   engaging, as well as emerging from communities of practice\n                   and intentionally engaging a public audience. Music\n                   librarians should also be aware of systemic challenges to\n                   creating and supporting digital projects because these\n                   issues are at the center of libraries supporting all types\n                   of digital scholarship.},\n    doi          = {10.1080/10588167.2017.1404301},\n    issn         = {15409503},\n    journal      = {Music Reference Services Quarterly},\n    keywords     = {Digital humanities,Digital scholarship,Music\n                   librarianship,Music theory,Musicology,musicology},\n    mendeley-tags= {musicology},\n    number       = {3-4},\n    pages        = {134--150},\n    publisher    = {Routledge},\n    url          = {https://doi.org/10.1080/10588167.2017.1404301},\n    volume       = {20}\n}\n\n
\n
\n\n\n
\n Musicologists and music theorists have traditionally been early adopters of technological tools to assist with research. The earliest digital humanities projects in musicology and music theory came directly out of humanities computing and quantitative analytical technologies developed in the 1980s, but newer projects created since the mid-2000s still reflect this past of algorithmic analysis and archival compilation, retrieval, and display. Computational and archival research is, currently, only one branch of digital humanities. The umbrella of digital humanities research now also includes digital publishing, philosophies of digital research, and “born digital” projects that cannot exist outside of a digital medium (e.g., virtual reality or 3D modeling). This shift in the digital humanities represents a move to a “bigger tent” that includes more types of projects. Musicological and musico-theoretical scholarship is slowly moving in this direction. Music librarians have been at the forefront of identifying and promoting new digital tools and archives, even though these projects have tended to remain at the periphery of musico-theoretical discourse. They should be on the lookout for “bigger tent” projects, such as medieval and renaissance projects like the Isabelle D'Este Archive, Opening the Geesebook, and the Experience of Worship. These projects are characterized by being iterative and multi-modally engaging, as well as emerging from communities of practice and intentionally engaging a public audience. Music librarians should also be aware of systemic challenges to creating and supporting digital projects because these issues are at the center of libraries supporting all types of digital scholarship.\n
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\n  \n 2016\n \n \n (27)\n \n \n
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\n \n\n \n \n \n \n \n \n Analysing Symbolic Music with Probabilistic Grammars.\n \n \n \n \n\n\n \n Abdallah, S.; Gold, N.; and Marsden, A.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 7, pages 157–189. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnalysingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InCollection{     abdallah.ea2016-analysing,\n    author       = {Abdallah, Samer and Gold, Nicolas and Marsden, Alan},\n    year         = {2016},\n    title        = {Analysing Symbolic Music with Probabilistic Grammars},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {7},\n    doi          = {10.1007/978-3-319-25931-4_7},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    pages        = {157--189},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_7}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
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\n \n\n \n \n \n \n \n \n Music Outlier Detection Using Multiple Sequence Alignment and Independent Ensembles.\n \n \n \n \n\n\n \n Bountouridis, D.; Koops, H. V.; Wiering, F.; and Veltkamp, R. C.\n\n\n \n\n\n\n In Amsaleg, L.; Houle, M. E.; and Schubert, E., editor(s), Proc. of 9th International Conference, SISAP 2016, pages 286–300, Tokyo, 2016. Springer Berlin Heidelberg\n \n\n\n\n
\n\n\n\n \n \n \"MusicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    bountouridis.ea2016-music,\n    author       = {Bountouridis, Dimitrios and Koops, Hendrik Vincent and\n                   Wiering, Frans and Veltkamp, Remco C.},\n    year         = {2016},\n    title        = {Music Outlier Detection Using Multiple Sequence Alignment\n                   and Independent Ensembles},\n    abstract     = {The automated retrieval of related music documents, such\n                   as cover songs or folk melodies belonging to the same\n                   tune, has been an important task in the field of Music\n                   Information Retrieval (MIR). Yet outlier detection, the\n                   process of identifying those documents that deviate\n                   significantly from the norm, has remained a rather\n                   unexplored topic. Pairwise comparison of music sequences\n                   (e.g. chord transcriptions, melodies), from which outlier\n                   detection can potentially emerge, has been always in the\n                   center of MIR research but the connection has remained\n                   uninvestigated. In this paper we firstly argue that for\n                   the analysis of musical collections of sequential data,\n                   outlier detection can benefit immensely from the\n                   advantages of Multiple Sequence Alignment (MSA). We show\n                   that certain MSA-based similarity methods can better\n                   separate inliers and outliers than the typical similarity\n                   based on pairwise comparisons. Secondly, aiming towards an\n                   unsupervised outlier detection method that is data-driven\n                   and robust enough to be generalizable across different\n                   music datasets, we show that ensemble approaches using an\n                   entropy-based diversity measure can outperform supervised\n                   alternatives.},\n    address      = {Tokyo},\n    booktitle    = {Proc. of 9th International Conference, SISAP 2016},\n    doi          = {10.1007/978-3-319-46759-7_22},\n    editor       = {Amsaleg, Laurent and Houle, Michael E. and Schubert,\n                   Erich},\n    isbn         = {9783319467597},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {286--300},\n    publisher    = {Springer Berlin Heidelberg},\n    url          = {http://link.springer.com/10.1007/978-3-319-46759-7_22}\n}\n\n
\n
\n\n\n
\n The automated retrieval of related music documents, such as cover songs or folk melodies belonging to the same tune, has been an important task in the field of Music Information Retrieval (MIR). Yet outlier detection, the process of identifying those documents that deviate significantly from the norm, has remained a rather unexplored topic. Pairwise comparison of music sequences (e.g. chord transcriptions, melodies), from which outlier detection can potentially emerge, has been always in the center of MIR research but the connection has remained uninvestigated. In this paper we firstly argue that for the analysis of musical collections of sequential data, outlier detection can benefit immensely from the advantages of Multiple Sequence Alignment (MSA). We show that certain MSA-based similarity methods can better separate inliers and outliers than the typical similarity based on pairwise comparisons. Secondly, aiming towards an unsupervised outlier detection method that is data-driven and robust enough to be generalizable across different music datasets, we show that ensemble approaches using an entropy-based diversity measure can outperform supervised alternatives.\n
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\n \n\n \n \n \n \n \n Perceiving Irony in Music: The Problem in Beethoven's String Quartets.\n \n \n \n\n\n \n Bourne, J.\n\n\n \n\n\n\n Music Theory Online, 22(3). 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          bourne2016-perceiving,\n    author       = {Bourne, Janet},\n    year         = {2016},\n    title        = {Perceiving Irony in Music: The Problem in Beethoven's\n                   String Quartets},\n    abstract     = {Hatten (1994) writes that if musical passages are\n                   “inappropriate to the context of the movement . . . an\n                   ironic interpretation would be one way to reconcile that\n                   inappropriateness as a compositional effect rather than a\n                   flaw” (185). Is there something systematic that prompts\n                   listeners to interpret musical “inappropriateness” as\n                   ironic? Building upon Hatten's work, this article explores\n                   how a listener might infer irony in Beethoven's music by\n                   drawing on cognitive principles and analogies shared by\n                   music and language. I create an analytical framework that\n                   draws conditions from language psychologists' empirical\n                   studies of verbal and situational irony (Colston 2001,\n                   Lucariello 1994). The first condition is a violation of\n                   expectations established through a norm or schema. I use\n                   Caplin's (1998) theory of formal function, Gjerdingen's\n                   (2007) schema theory, and Hepokoski and Darcy's (2006)\n                   Sonata Theory to measure violation of expectation as\n                   defined by Beethoven and his audience's shared stylistic\n                   knowledge. Since listeners develop expectations in music\n                   simply by listening (Meyer 1956), this paper incorporates\n                   “common ground,” Clark's (1996) term for the\n                   information, knowledge, and cultural norms that the\n                   composer and listener share. The second condition is\n                   blatantly failing to fulfill one or more of the\n                   “maxims” defined by the linguist H.P. Grice (1975),\n                   who argues that a person implicitly follows the maxims in\n                   any “cooperative” conversation. I apply this framework\n                   to analyze three Beethoven string quartet movements that\n                   Hatten and others have described as “ironic”: op.\n                   95/iv, op. 131/v, and op. 130/i. I close by discussing\n                   implications for musical communication as a whole.\n                   [ABSTRACT FROM AUTHOR]},\n    doi          = {10.30535/mto.22.3.2},\n    issn         = {1067-3040},\n    journal      = {Music Theory Online},\n    keywords     = {aesthetics,alla breve,coda,contradiction,discourse\n                   marker,irony,literature,music\n                   analysis,musical,pathos,philosophy,situational ethics},\n    mendeley-tags= {music analysis},\n    number       = {3},\n    volume       = {22}\n}\n\n
\n
\n\n\n
\n Hatten (1994) writes that if musical passages are “inappropriate to the context of the movement . . . an ironic interpretation would be one way to reconcile that inappropriateness as a compositional effect rather than a flaw” (185). Is there something systematic that prompts listeners to interpret musical “inappropriateness” as ironic? Building upon Hatten's work, this article explores how a listener might infer irony in Beethoven's music by drawing on cognitive principles and analogies shared by music and language. I create an analytical framework that draws conditions from language psychologists' empirical studies of verbal and situational irony (Colston 2001, Lucariello 1994). The first condition is a violation of expectations established through a norm or schema. I use Caplin's (1998) theory of formal function, Gjerdingen's (2007) schema theory, and Hepokoski and Darcy's (2006) Sonata Theory to measure violation of expectation as defined by Beethoven and his audience's shared stylistic knowledge. Since listeners develop expectations in music simply by listening (Meyer 1956), this paper incorporates “common ground,” Clark's (1996) term for the information, knowledge, and cultural norms that the composer and listener share. The second condition is blatantly failing to fulfill one or more of the “maxims” defined by the linguist H.P. Grice (1975), who argues that a person implicitly follows the maxims in any “cooperative” conversation. I apply this framework to analyze three Beethoven string quartet movements that Hatten and others have described as “ironic”: op. 95/iv, op. 131/v, and op. 130/i. I close by discussing implications for musical communication as a whole. [ABSTRACT FROM AUTHOR]\n
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\n \n\n \n \n \n \n \n \n Musical Stylometry, Machine Learning, and Attribution Studies: A Semi-Supervised Approach to the Works of Josquin.\n \n \n \n \n\n\n \n Brinkman, A.; Shanahan, D.; and Sapp, C. S.\n\n\n \n\n\n\n In Proceedings of the International Conference on Music Perception and Cognition, pages 91–97, San Francisco, 2016. \n \n\n\n\n
\n\n\n\n \n \n \"MusicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    brinkman.ea2016-musical,\n    author       = {Brinkman, Alan and Shanahan, Daniel and Sapp, Craig\n                   Stuart},\n    year         = {2016},\n    title        = {Musical {Stylometry}, {Machine} {Learning}, and\n                   {Attribution} {Studies}: {A} {Semi}-{Supervised}\n                   {Approach} to the {Works} of {Josquin}},\n    address      = {San Francisco},\n    url          = {http://icmpc.org/icmpc14/files/ICMPC14_Proceedings.pdf},\n    abstract     = {Compositional authorship is often assigned though factors\n                   external to the musical text, such as biographical records\n                   and surveys of source attributions; however, such\n                   methodologies often fall short and are potentially\n                   unreliable. On the other hand, determining compositional\n                   authorship through internal factors—through stylistic\n                   traits of composers derived from the music itself—is\n                   often fraught with errors and biases. One of the\n                   underlying assumptions in the field of stylometry is that,\n                   while it is difficult for humans to perform a truly\n                   unbiased analysis of authorial attribution, computational\n                   methods can provide clearer and more objective guidelines\n                   than would otherwise be apparent to readers or listeners,\n                   and thus might provide corroboration or clues for further\n                   investigation. This paper discusses machine-learning\n                   approaches for evaluating attribution for compositions by\n                   Josquin des Prez. We explore musical characteristics such\n                   as melodic sequences, counterpoint motion, rhythmic\n                   variability, and other entry measures to search for\n                   features inherent to a composer's works or style, and we\n                   hope that employing such an approach—one that explicitly\n                   states which factors led to the decision-making\n                   process—can serve to inform scholars looking at other\n                   works and composers.},\n    booktitle    = {Proceedings of the {International} {Conference} on\n                   {Music} {Perception} and {Cognition}},\n    keywords     = {Computational Musicology},\n    pages        = {91--97}\n}\n\n
\n
\n\n\n
\n Compositional authorship is often assigned though factors external to the musical text, such as biographical records and surveys of source attributions; however, such methodologies often fall short and are potentially unreliable. On the other hand, determining compositional authorship through internal factors—through stylistic traits of composers derived from the music itself—is often fraught with errors and biases. One of the underlying assumptions in the field of stylometry is that, while it is difficult for humans to perform a truly unbiased analysis of authorial attribution, computational methods can provide clearer and more objective guidelines than would otherwise be apparent to readers or listeners, and thus might provide corroboration or clues for further investigation. This paper discusses machine-learning approaches for evaluating attribution for compositions by Josquin des Prez. We explore musical characteristics such as melodic sequences, counterpoint motion, rhythmic variability, and other entry measures to search for features inherent to a composer's works or style, and we hope that employing such an approach—one that explicitly states which factors led to the decision-making process—can serve to inform scholars looking at other works and composers.\n
\n\n\n
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\n \n\n \n \n \n \n \n Music Information Retrieval.\n \n \n \n\n\n \n Burgoyne, J. A.; Fujinaga, I.; and Downie, J S.\n\n\n \n\n\n\n In A New Companion to Digital Humanities, pages 213–228. John Wiley & Sons, Ltd, 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InCollection{     burgoyne.ea2016-music,\n    author       = {Burgoyne, John Ashley and Fujinaga, Ichiro and Downie, J\n                   Stephen},\n    year         = {2016},\n    title        = {Music {Information} {Retrieval}},\n    language     = {en},\n    booktitle    = {A {New} {Companion} to {Digital} {Humanities}},\n    publisher    = {John Wiley \\& Sons, Ltd},\n    collaborator = {Schreibman, Susan and Siemens, Ray},\n    pages        = {213--228}\n}\n\n
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\n \n\n \n \n \n \n \n The Continuous Exposition and the Concept of Subordinate Theme.\n \n \n \n\n\n \n Caplin, W. E.; and Martin, N. J.\n\n\n \n\n\n\n Music Analysis, 35(1): 4–43. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          caplin.ea2016-continuous,\n    author       = {Caplin, William Earl and Martin, Nathan John},\n    year         = {2016},\n    title        = {The Continuous Exposition and the Concept of Subordinate\n                   Theme},\n    abstract     = {James Hepokoski and Warren Darcy's Sonata Theory promotes\n                   a fundamental distinction between sonata expositions that\n                   are either two-part or continuous. We contend that this\n                   binary opposition misconstrues the commonality of formal\n                   procedures operative in Classical sonata form. Advocating\n                   a form-functional approach, we hold that all sonata\n                   expositions contain a subordinate theme (or at least\n                   sufficient functional elements of such a theme), even if\n                   the boundary between the transition and subordinate theme\n                   is obscured. We illustrate three categories of such a\n                   blurred boundary: (1) the transition lacks a functional\n                   ending but the subordinate theme still brings an\n                   initiating function of some kind; (2) the transition ends\n                   normally but the subordinate theme lacks a clear\n                   beginning; and (3) the transition lacks an ending and the\n                   subordinate theme lacks a beginning, thus effecting a\n                   complete fusion of these thematic functions. We extend\n                   these considerations to another formal type - minuet form\n                   - in order to place the technique of fusion as it arises\n                   in sonata-form expositions in a broader perspective. In\n                   further comparing a theory of formal functions to Sonata\n                   Theory, we invoke thesonata clockmetaphor, first\n                   introduced by Hepokoski and Darcy, and show that our\n                   respective clocks have differenthourmarkers and run at\n                   different speeds. We conclude by examining some of the\n                   main conceptual differences that account for the divergent\n                   views of expositional structures offered by Sonata Theory\n                   and a theory of formal functions, arguing against the\n                   former's claim that the medial caesura is a necessary\n                   condition for the appearance of a subordinate theme.},\n    doi          = {10.1111/musa.12060},\n    issn         = {02625245},\n    journal      = {Music Analysis},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {1},\n    pages        = {4--43},\n    volume       = {35}\n}\n\n
\n
\n\n\n
\n James Hepokoski and Warren Darcy's Sonata Theory promotes a fundamental distinction between sonata expositions that are either two-part or continuous. We contend that this binary opposition misconstrues the commonality of formal procedures operative in Classical sonata form. Advocating a form-functional approach, we hold that all sonata expositions contain a subordinate theme (or at least sufficient functional elements of such a theme), even if the boundary between the transition and subordinate theme is obscured. We illustrate three categories of such a blurred boundary: (1) the transition lacks a functional ending but the subordinate theme still brings an initiating function of some kind; (2) the transition ends normally but the subordinate theme lacks a clear beginning; and (3) the transition lacks an ending and the subordinate theme lacks a beginning, thus effecting a complete fusion of these thematic functions. We extend these considerations to another formal type - minuet form - in order to place the technique of fusion as it arises in sonata-form expositions in a broader perspective. In further comparing a theory of formal functions to Sonata Theory, we invoke thesonata clockmetaphor, first introduced by Hepokoski and Darcy, and show that our respective clocks have differenthourmarkers and run at different speeds. We conclude by examining some of the main conceptual differences that account for the divergent views of expositional structures offered by Sonata Theory and a theory of formal functions, arguing against the former's claim that the medial caesura is a necessary condition for the appearance of a subordinate theme.\n
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\n \n\n \n \n \n \n \n \n Using Geometric Symbolic Fingerprinting to Discover Distinctive Patterns in Polyphonic Music Corpora.\n \n \n \n \n\n\n \n Collins, T.; Arzt, A.; Frostel, H.; and Widmer, G.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 17, pages 445–474. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"UsingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     collins.ea2016-using,\n    author       = {Collins, Tom and Arzt, Andreas and Frostel, Harald and\n                   Widmer, Gerhard},\n    year         = {2016},\n    title        = {Using Geometric Symbolic Fingerprinting to Discover\n                   Distinctive Patterns in Polyphonic Music Corpora},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {17},\n    doi          = {10.1007/978-3-319-25931-4_17},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {445--474},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_17}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
\n\n\n
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\n \n\n \n \n \n \n \n Algorithmique et technologies numériques dans la notation musicale.\n \n \n \n\n\n \n Couprie, P.\n\n\n \n\n\n\n In Musiques Orales, leur notation et encodage numérique, pages 99–115. Les éditions de l'immatériel, 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InCollection{     couprie2016-algorithmique,\n    author       = {Couprie, Pierre},\n    year         = {2016},\n    title        = {Algorithmique et technologies numériques dans la\n                   notation musicale},\n    language     = {fr},\n    booktitle    = {Musiques {Orales}, leur notation et encodage\n                   num\\'{e}rique},\n    publisher    = {Les éditions de l'immatériel},\n    collaborator = {Martin, Sylvaine Leblond},\n    pages        = {99--115}\n}\n\n
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\n \n\n \n \n \n \n \n Modelagem e particionamento de Unidades Musicais Sistêmicas.\n \n \n \n\n\n \n Fortes, R.\n\n\n \n\n\n\n Ph.D. Thesis, Universidade Federal do Rio de Janeiro, 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@PhDThesis{        fortes2016-modelagem,\n    author       = {Rafael Fortes},\n    year         = {2016},\n    title        = {Modelagem e particionamento de Unidades Musicais\n                   Sistêmicas},\n    school       = {Universidade Federal do Rio de Janeiro},\n    type         = {Master's Thesis}\n}\n\n
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\n \n\n \n \n \n \n \n \n Implementing Methods for Analysing Music Based on Lerdahl and Jackendoff's Generative Theory of Tonal Music.\n \n \n \n \n\n\n \n Hamanaka, M.; Hirata, K.; and Tojo, S.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 9, pages 221–249. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ImplementingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     hamanaka.ea2016-implementing,\n    author       = {Hamanaka, Masatoshi and Hirata, Keiji and Tojo, Satoshi},\n    year         = {2016},\n    title        = {Implementing Methods for Analysing Music Based on Lerdahl\n                   and Jackendoff's Generative Theory of Tonal Music},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {9},\n    doi          = {10.1007/978-3-319-25931-4_9},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {221--249},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_9}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Composer Classification Models for Music-Theory Building.\n \n \n \n \n\n\n \n Herremans, D.; Martens, D.; and Sörensen, K.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 14, pages 369–392. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ComposerPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     herremans.ea2016-composer,\n    author       = {Herremans, Dorien and Martens, David and S{\\"{o}}rensen,\n                   Kenneth},\n    year         = {2016},\n    title        = {Composer Classification Models for Music-Theory\n                   Building},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {14},\n    doi          = {10.1007/978-3-319-25931-4_14},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {369--392},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_14}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
\n\n\n
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\n \n\n \n \n \n \n \n \n An Algebraic Approach to Time-Span Reduction.\n \n \n \n \n\n\n \n Hirata, K.; Tojo, S.; and Hamanaka, M.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 10, pages 251–270. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     hirata.ea2016-algebraic,\n    author       = {Hirata, Keiji and Tojo, Satoshi and Hamanaka, Masatoshi},\n    year         = {2016},\n    title        = {An Algebraic Approach to Time-Span Reduction},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {10},\n    doi          = {10.1007/978-3-319-25931-4_10},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {251--270},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_10}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
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\n \n\n \n \n \n \n \n Are Stopped Strings Preferred in Sad Music?.\n \n \n \n\n\n \n Huron, D.; and Trevor, C.\n\n\n \n\n\n\n Empirical Musicology Review, 11(2): 261. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          huron.ea2016-are,\n    author       = {Huron, David and Trevor, Caitlyn},\n    year         = {2016},\n    title        = {Are Stopped Strings Preferred in Sad Music?},\n    abstract     = {String instruments may be played either with open strings\n                   (where the string vibrates between the bridge and a hard\n                   wooden nut) or with stopped strings (where the string\n                   vibrates between the bridge and a performer's finger\n                   pressed against the fingerboard). Compared with open\n                   strings, stopped strings permit the use of vibrato and\n                   exhibit a darker timbre. Inspired by research on the\n                   timbre of sad speech, we test whether there is a tendency\n                   to use stopped strings in nominally sad music.\n                   Specifically, we compare the proportion of potentially\n                   open-to-stopped strings in a sample of slow, minor-mode\n                   movements with matched major-mode movements. By way of\n                   illustration, a preliminary analysis of Samuel Barber's\n                   famous Adagio from his Opus 11 string quartet shows that\n                   the selected key (B-flat minor) provides the optimum key\n                   for minimizing open string tones. However, examination of\n                   a broader controlled sample of quartet movements by Haydn,\n                   Mozart and Beethoven failed to exhibit the conjectured\n                   relationship. Instead, major-mode movements were found to\n                   avoid possible open strings more than slow minor-mode\n                   movements.},\n    doi          = {10.18061/emr.v11i2.4968},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {barber,music analysis with computers,s adagio,sad\n                   music,stopped strings,string instruments},\n    mendeley-tags= {music analysis with computers},\n    number       = {2},\n    pages        = {261},\n    volume       = {11}\n}\n\n
\n
\n\n\n
\n String instruments may be played either with open strings (where the string vibrates between the bridge and a hard wooden nut) or with stopped strings (where the string vibrates between the bridge and a performer's finger pressed against the fingerboard). Compared with open strings, stopped strings permit the use of vibrato and exhibit a darker timbre. Inspired by research on the timbre of sad speech, we test whether there is a tendency to use stopped strings in nominally sad music. Specifically, we compare the proportion of potentially open-to-stopped strings in a sample of slow, minor-mode movements with matched major-mode movements. By way of illustration, a preliminary analysis of Samuel Barber's famous Adagio from his Opus 11 string quartet shows that the selected key (B-flat minor) provides the optimum key for minimizing open string tones. However, examination of a broader controlled sample of quartet movements by Haydn, Mozart and Beethoven failed to exhibit the conjectured relationship. Instead, major-mode movements were found to avoid possible open strings more than slow minor-mode movements.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Corpus COFLA: A Research Corpus for the Computational Study of Flamenco Music.\n \n \n \n \n\n\n \n Kroher, N.; Díaz-Báñez, J.; Mora, J.; and Gómez, E.\n\n\n \n\n\n\n Journal on Computing and Cultural Heritage, 9(2): 1–21. may 2016.\n \n\n\n\n
\n\n\n\n \n \n \"CorpusPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          kroher.ea2016-corpus,\n    author       = {Kroher, Nadine and D{\\'{i}}az-B{\\'{a}}{\\~{n}}ez,\n                   Jos{\\'{e}}-Miguel and Mora, Joaquin and G{\\'{o}}mez, Emilia},\n    year         = {2016},\n    title        = {Corpus COFLA: A Research Corpus for the Computational\n                   Study of Flamenco Music},\n    abstract     = {Flamenco is a music tradition from Southern Spain that\n                   attracts a growing community of enthusiasts around the\n                   world. Its unique melodic and rhythmic elements, the\n                   typically spontaneous and improvised interpretation, and\n                   its diversity regarding styles make this still largely\n                   undocumented art form a particularly interesting material\n                   for musicological studies. In prior works, it has already\n                   been demonstrated that research on computational analysis\n                   of flamenco music, despite it being a relatively new\n                   field, can provide powerful tools for the discovery and\n                   diffusion of this genre. In this article, we present\n                   corpusCOFLA, a data framework for the development of such\n                   computational tools. The proposed collection of audio\n                   recordings and metadata serves as a pool for creating\n                   annotated subsets that can be used in development and\n                   evaluation of algorithms for specific music information\n                   retrieval tasks. First, we describe the design criteria\n                   for the corpus creation and then provide various examples\n                   of subsets drawn from the corpus. We showcase possible\n                   research applications in the context of computational\n                   study of flamenco music and give perspectives regarding\n                   further development of the corpus.},\n    archiveprefix= {arXiv},\n    arxivid      = {1510.04029},\n    doi          = {10.1145/2875428},\n    eprint       = {1510.04029},\n    issn         = {1556-4673},\n    journal      = {Journal on Computing and Cultural Heritage},\n    keywords     = {Computational ethnomusicology,Flamenco,Research\n                   corpus,computational musicology},\n    mendeley-tags= {computational musicology},\n    month        = {may},\n    number       = {2},\n    pages        = {1--21},\n    url          = {https://dl.acm.org/doi/10.1145/2875428},\n    volume       = {9}\n}\n\n
\n
\n\n\n
\n Flamenco is a music tradition from Southern Spain that attracts a growing community of enthusiasts around the world. Its unique melodic and rhythmic elements, the typically spontaneous and improvised interpretation, and its diversity regarding styles make this still largely undocumented art form a particularly interesting material for musicological studies. In prior works, it has already been demonstrated that research on computational analysis of flamenco music, despite it being a relatively new field, can provide powerful tools for the discovery and diffusion of this genre. In this article, we present corpusCOFLA, a data framework for the development of such computational tools. The proposed collection of audio recordings and metadata serves as a pool for creating annotated subsets that can be used in development and evaluation of algorithms for specific music information retrieval tasks. First, we describe the design criteria for the corpus creation and then provide various examples of subsets drawn from the corpus. We showcase possible research applications in the context of computational study of flamenco music and give perspectives regarding further development of the corpus.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Analysing Music with Point-Set Compression Algorithms.\n \n \n \n \n\n\n \n Meredith, D.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 13, pages 335–366. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnalysingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     meredith2016-analysing,\n    author       = {Meredith, David},\n    year         = {2016},\n    title        = {Analysing Music with Point-Set Compression Algorithms},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {13},\n    doi          = {10.1007/978-3-319-25931-4_13},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {335--366},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_13}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Data-based melody generation through multi-objective evolutionary computation.\n \n \n \n \n\n\n \n Ponce de León, P. J.; Iñesta, J. M.; Calvo-Zaragoza, J.; and Rizo, D.\n\n\n \n\n\n\n Journal of Mathematics and Music, 10(2): 173–192. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Data-basedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          ponce-de-leon.ea2016-data-based,\n    author       = {{Ponce de Le{\\'{o}}n}, Pedro J. and I{\\~{n}}esta,\n                   Jos{\\'{e}} M. and Calvo-Zaragoza, Jorge and Rizo, David},\n    year         = {2016},\n    title        = {Data-based melody generation through multi-objective\n                   evolutionary computation},\n    abstract     = {Genetic-based composition algorithms are able to explore\n                   an immense space of possibilities, but the main difficulty\n                   has always been the implementation of the selection\n                   process. In this work, sets of melodies are utilized for\n                   training a machine learning approach to compute fitness,\n                   based on different metrics. The fitness of a candidate is\n                   provided by combining the metrics, but their values can\n                   range through different orders of magnitude and evolve in\n                   different ways, which makes it hard to combine these\n                   criteria. In order to solve this problem, a\n                   multi-objective fitness approach is proposed, in which the\n                   best individuals are those in the Pareto front of the\n                   multi-dimensional fitness space. Melodic trees are also\n                   proposed as a data structure for chromosomic\n                   representation of melodies and genetic operators are\n                   adapted to them. Some experiments have been carried out\n                   using a graphical interface prototype that allows one to\n                   explore the creative capabilities of the proposed system.\n                   An Online Supplement is provided and can be accessed at\n                   http://dx.doi.org/10.1080/17459737.2016.1188171, where the\n                   reader can find some technical details, information about\n                   the data used, generated melodies, and additional\n                   information about the developed prototype and its\n                   performance.},\n    doi          = {10.1080/17459737.2016.1188171},\n    issn         = {17459745},\n    journal      = {Journal of Mathematics and Music},\n    keywords     = {algorithmic composition,composition,evolutionary\n                   algorithms,machine learning,melody,multi-objective\n                   optimization,tree representation},\n    mendeley-tags= {algorithmic composition},\n    number       = {2},\n    pages        = {173--192},\n    url          = {https://doi.org/10.1080/17459737.2016.1188171},\n    volume       = {10}\n}\n\n
\n
\n\n\n
\n Genetic-based composition algorithms are able to explore an immense space of possibilities, but the main difficulty has always been the implementation of the selection process. In this work, sets of melodies are utilized for training a machine learning approach to compute fitness, based on different metrics. The fitness of a candidate is provided by combining the metrics, but their values can range through different orders of magnitude and evolve in different ways, which makes it hard to combine these criteria. In order to solve this problem, a multi-objective fitness approach is proposed, in which the best individuals are those in the Pareto front of the multi-dimensional fitness space. Melodic trees are also proposed as a data structure for chromosomic representation of melodies and genetic operators are adapted to them. Some experiments have been carried out using a graphical interface prototype that allows one to explore the creative capabilities of the proposed system. An Online Supplement is provided and can be accessed at http://dx.doi.org/10.1080/17459737.2016.1188171, where the reader can find some technical details, information about the data used, generated melodies, and additional information about the developed prototype and its performance.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Interactive Melodic Analysis.\n \n \n \n \n\n\n \n Rizo, D.; Illescas, P. R.; and Iñesta, J. M.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 8, pages 191–219. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"InteractivePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InCollection{     rizo.ea2016-interactive,\n    author       = {Rizo, David and Illescas, Pl{\\'{a}}cido R. and\n                   I{\\~{n}}esta, Jos{\\'{e}} M.},\n    year         = {2016},\n    title        = {Interactive Melodic Analysis},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {8},\n    doi          = {10.1007/978-3-319-25931-4_8},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    pages        = {191--219},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_8}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n A standard format proposal for hierarchical analyses and representations.\n \n \n \n \n\n\n \n Rizo, D.; and Marsden, A.\n\n\n \n\n\n\n In Proceedings of the 3rd International workshop on Digital Libraries for Musicology - DLfM 2016, pages 25–32, New York, New York, USA, 2016. ACM Press\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@InProceedings{    rizo.ea2016-standard,\n    author       = {Rizo, David and Marsden, Alan},\n    year         = {2016},\n    title        = {A standard format proposal for hierarchical analyses and\n                   representations},\n    abstract     = {In the realm of digital musicology, standardizations\n                   efforts to date have mostly concentrated on the\n                   representation of music. Analyses of music are\n                   increasingly being generated or communicated by digital\n                   means. We demonstrate that the same arguments for the\n                   desirability of standardization in the representation of\n                   music apply also to the representation of analyses of\n                   music: proper preservation, sharing of data, and\n                   facilitation of digital processing. We concentrate here on\n                   analyses which can be described as hierarchical and show\n                   that this covers a broad range of existing analytical\n                   formats. We propose an extension of MEI (Music Encoding\n                   Initiative) to allow the encoding of analyses\n                   unambiguously associated with and aligned to a\n                   representation of the music analysed, making use of\n                   existing mechanisms within MEI's parent TEI (Text Encoding\n                   Initiative) for the representation of trees and graphs.},\n    address      = {New York, New York, USA},\n    booktitle    = {Proceedings of the 3rd International workshop on Digital\n                   Libraries for Musicology - DLfM 2016},\n    doi          = {10.1145/2970044.2970046},\n    isbn         = {9781450347518},\n    keywords     = {Encodings,Music analysis,Music\n                   representations,Standards,computer and music},\n    mendeley-tags= {computer and music},\n    pages        = {25--32},\n    publisher    = {ACM Press},\n    url          = {http://dl.acm.org/citation.cfm?doid=2970044.2970046}\n}\n\n
\n
\n\n\n
\n In the realm of digital musicology, standardizations efforts to date have mostly concentrated on the representation of music. Analyses of music are increasingly being generated or communicated by digital means. We demonstrate that the same arguments for the desirability of standardization in the representation of music apply also to the representation of analyses of music: proper preservation, sharing of data, and facilitation of digital processing. We concentrate here on analyses which can be described as hierarchical and show that this covers a broad range of existing analytical formats. We propose an extension of MEI (Music Encoding Initiative) to allow the encoding of analyses unambiguously associated with and aligned to a representation of the music analysed, making use of existing mechanisms within MEI's parent TEI (Text Encoding Initiative) for the representation of trees and graphs.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Contour Algorithms Review.\n \n \n \n \n\n\n \n Sampaio, M.; and Kroger, P.\n\n\n \n\n\n\n MusMat - Brazilian Journal of Music and Mathematics, 1(1): 72–85. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ContourPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          sampaio.ea2016-contour,\n    author       = {{Sampaio}, {Marcos da Silva} and Kroger, Pedro},\n    year         = {2016},\n    title        = {Contour Algorithms Review},\n    abstract     = {In this paper, we present some problems of two Music\n                   Contour Relations Theory operations algorithms: the\n                   Refinement of Contour Reduction Algorithm, which was\n                   developed by Rob Schultz, and the Equivalence Contour\n                   Class Prime Form algorithm, which was developed by\n                   Elizabeth Marvin and Paul Laprade. We also propose two\n                   alternative algorithms to solve these problems.},\n    journal      = {MusMat - Brazilian Journal of Music and Mathematics},\n    keywords     = {algorithm,equivalent contour classes,music contour,music\n                   contour theory,reduction algorithm},\n    mendeley-tags= {music contour},\n    number       = {1},\n    pages        = {72--85},\n    url          = {https://grupomusmat.files.wordpress.com/2016/12/07-sampaio.pdf},\n    volume       = {1}\n}\n\n
\n
\n\n\n
\n In this paper, we present some problems of two Music Contour Relations Theory operations algorithms: the Refinement of Contour Reduction Algorithm, which was developed by Rob Schultz, and the Equivalence Contour Class Prime Form algorithm, which was developed by Elizabeth Marvin and Paul Laprade. We also propose two alternative algorithms to solve these problems.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A new companion to Digital Humanities.\n \n \n \n\n\n \n Schreibman, S.; Siemens, R.; and Unsworth, J.,\n editors.\n \n\n\n \n\n\n\n John Wiley & Sons Ltd, West Sussex, England, 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             schreibman.ea2016-new,\n    year         = {2016},\n    title        = {A new companion to Digital Humanities},\n    address      = {West Sussex, England},\n    editor       = {Schreibman, Susan and Siemens, Ray and Unsworth, Johm},\n    isbn         = {9781118680599},\n    keywords     = {computer},\n    mendeley-tags= {computer},\n    publisher    = {John Wiley \\& Sons Ltd}\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Normalizing Musical Contour Theory.\n \n \n \n \n\n\n \n Schultz, R. D.\n\n\n \n\n\n\n Journal of Music Theory, 60(1): 23–50. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"NormalizingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          schultz2016-normalizing,\n    author       = {Schultz, Rob D.},\n    year         = {2016},\n    title        = {Normalizing Musical Contour Theory},\n    doi          = {10.1215/00222909-3448746},\n    issn         = {0022-2909},\n    journal      = {Journal of Music Theory},\n    keywords     = {149,1995,50,advantages that numerical\n                   representa-,analytical notation,contour,elizabeth west\n                   marvin,has cited three distinct,melody,music\n                   contour,normalization,numerical representation of\n                   contour,of musical contour theory,pitch,rhythm,shed in the\n                   development,the advent of the,was a water-},\n    mendeley-tags= {music contour},\n    number       = {1},\n    pages        = {23--50},\n    url          = {http://jmt.dukejournals.org/lookup/doi/10.1215/00222909-3448746},\n    volume       = {60}\n}\n\n
\n
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\n \n\n \n \n \n \n \n \n A Wavelet-Based Approach to Pattern Discovery in Melodies.\n \n \n \n \n\n\n \n Velarde, G.; Meredith, D.; and Weyde, T.\n\n\n \n\n\n\n In Meredith, D., editor(s), Computational Music Analysis, 12, pages 303–333. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     velarde.ea2016-wavelet-based,\n    author       = {Velarde, Gissel and Meredith, David and Weyde, Tillman},\n    year         = {2016},\n    title        = {A Wavelet-Based Approach to Pattern Discovery in\n                   Melodies},\n    abstract     = {This book provides an in-depth introduction and overview\n                   of current research in computational music analysis. Its\n                   seventeen chapters, written by leading researchers,\n                   collectively represent the diversity as well as the\n                   technical and philosophical sophistication of the work\n                   being done today in this intensely interdisciplinary\n                   field. A broad range of approaches are presented,\n                   employing techniques originating in disciplines such as\n                   linguistics, information theory, information retrieval,\n                   pattern recognition, machine learning, topology, algebra\n                   and signal processing. Many of the methods described draw\n                   on well-established theories in music theory and analysis,\n                   such as Forte's pitch-class set theory, Schenkerian\n                   analysis, the methods of semiotic analysis developed by\n                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n                   Theory of Tonal Music. The book is divided into six parts,\n                   covering methodological issues, harmonic and pitch-class\n                   set analysis, form and voice-separation, grammars and\n                   hierarchical reduction, motivic analysis and pattern\n                   discovery and, finally, classification and the discovery\n                   of distinctive patterns. As a detailed and up-to-date\n                   picture of current research in computational music\n                   analysis, the book provides an invaluable resource for\n                   researchers, teachers and students in music theory and\n                   analysis, computer science, music information retrieval\n                   and related disciplines. It also provides a\n                   state-of-the-art reference for practitioners in the music\n                   technology industry.},\n    address      = {Cham},\n    booktitle    = {Computational Music Analysis},\n    chapter      = {12},\n    doi          = {10.1007/978-3-319-25931-4_12},\n    editor       = {Meredith, David},\n    isbn         = {9783319259314},\n    issn         = {0098-7484},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {303--333},\n    pmid         = {1689},\n    publisher    = {Springer International Publishing},\n    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_12}\n}\n\n
\n
\n\n\n
\n This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Symbolic Melodic Similarity: State of the Art and Future Challenges.\n \n \n \n \n\n\n \n Velardo, V.; Vallati, M.; and Jan, S.\n\n\n \n\n\n\n Computer Music Journal, 40(1): 10–24. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SymbolicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          velardo.ea2016-symbolic,\n    author       = {Velardo, Valerio and Vallati, Mauro and Jan, Steven},\n    year         = {2016},\n    title        = {Symbolic Melodic Similarity: State of the Art and Future\n                   Challenges},\n    abstract     = {The invention of software in the mid-20th century was as\n                   big a breakthrough for modern humans as the mastery over\n                   fire was for our prehistoric ancestors; the addition of\n                   cognitive fluidity to hardware has resulted in an\n                   explosion of experimentation and creativity (which also\n                   poses some challenges). As is the case with any new\n                   technology, humans immediately set about using software to\n                   connect with one another and extend our networks of\n                   distributed cognition. Computer musicians are uniquely\n                   positioned to predict the future by composing it and\n                   coding it, because as a group we combine the imagination\n                   and daring of artists with the technology that can make\n                   the imaginary real.},\n    isbn         = {8187672641},\n    issn         = {1531-5169},\n    journal      = {Computer Music Journal},\n    keywords     = {kyma,music similarity,systems},\n    mendeley-tags= {music similarity},\n    number       = {1},\n    pages        = {10--24},\n    url          = {http://www.mitpressjournals.org/doi/pdf/10.1162/COMJ_a_00359},\n    volume       = {40}\n}\n\n
\n
\n\n\n
\n The invention of software in the mid-20th century was as big a breakthrough for modern humans as the mastery over fire was for our prehistoric ancestors; the addition of cognitive fluidity to hardware has resulted in an explosion of experimentation and creativity (which also poses some challenges). As is the case with any new technology, humans immediately set about using software to connect with one another and extend our networks of distributed cognition. Computer musicians are uniquely positioned to predict the future by composing it and coding it, because as a group we combine the imagination and daring of artists with the technology that can make the imaginary real.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Examining Contrasting Expressive Content within First and Second Musical Themes.\n \n \n \n \n\n\n \n Warrenburg, L. A.\n\n\n \n\n\n\n Ph.D. Thesis, The Ohio State University, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ExaminingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@PhDThesis{        warrenburg2016-examining,\n    author       = {Warrenburg, Lindsay Alison},\n    year         = {2016},\n    title        = {Examining Contrasting Expressive Content within First and\n                   Second Musical Themes},\n    pages        = {2016},\n    school       = {The Ohio State University},\n    type         = {Master Thesis},\n    url          = {https://etd.ohiolink.edu/pg_10?::NO:10:P10_ETD_SUBID:114166}\n}\n\n
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\n \n\n \n \n \n \n \n \n Computational Methods for Tonality-Based Style Analysis of Classical Music Audio Recordings.\n \n \n \n \n\n\n \n Weiß, C.\n\n\n \n\n\n\n Ph.D. Thesis, Technische Universität Ilmenau, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@PhDThesis{        wei2016-computational,\n    author       = {Wei{\\ss}, Christof},\n    year         = {2016},\n    title        = {Computational Methods for Tonality-Based Style Analysis\n                   of Classical Music Audio Recordings},\n    abstract     = {With the tremendously growing impact of digital\n                   technology, the ways of accessing music crucially changed.\n                   Nowadays, streaming services, download platforms, and\n                   private archives provide a large amount of music\n                   recordings to listeners. As tools for organizing and\n                   browsing such collections, automatic methods have become\n                   important. In the area of Music Informa- tion Retrieval,\n                   researchers are developing algorithms for analyzing and\n                   comparing music data with respect to musical\n                   characteristics. One typical application scenario is the\n                   classification of music recordings according to categories\n                   such as musical genres. In this thesis, we approach such\n                   classification problems with the goal of discriminating\n                   subgenres within Western classical music. In particular,\n                   we focus on typical categories such as historical periods\n                   or individual composers. From a musicological point of\n                   view, this classi- fication problem relates to the\n                   question of musical style, which constitutes a rather\n                   ill-defined and abstract concept. Usually, musicologists\n                   analyze musical scores in a manual fashion in order to\n                   acquire knowledge about style and its determining factors.\n                   This thesis contributes with computational methods for\n                   realizing such analyses on comprehensive corpora of audio\n                   recordings. Though it is hard to extract explicit\n                   information such as note events from audio data, the\n                   computational analysis of audio recordings might bear\n                   great potential for musi- cological research. One reason\n                   for this is the limited availability of symbolic scores in\n                   high quality. The style analysis experiments presented in\n                   this thesis focus on the fields of harmony and tonality.\n                   In the first step, we use signal processing techniques for\n                   computing chroma representations of the audio data. These\n                   semantic “mid-level” representations capture the pitch\n                   class content of an audio recording in a robust way and,\n                   thus, constitute a suitable starting point for subsequent\n                   processing steps. From such chroma representations, we\n                   derive measures for quantitatively describing stylistic\n                   properties of the music. Since chroma features suppress\n                   timbral characteristics to a certain extent, we hope to\n                   achieve invariance to timbre and instrumentation for our\n                   analysis methods. Inspired by the characteristics of the\n                   chroma representations, we model in this thesis specific\n                   concepts from music theory and propose algorithms to\n                   measure the occurence of certain tonal structures in audio\n                   recordings. One of the proposed methods aims at estimating\n                   the global key of a piece by considering the particular\n                   role of the final chord. Another contribution of this\n                   thesis is an automatic method to visualize modulations\n                   regarding diatonic scales as well as scale types over the\n                   course of a piece. Furthermore, we propose novel\n                   techniques for estimating the presence of specific\n                   interval and chord types and for measuring more abstract\n                   notions such as tonal complexity. In first experiments, we\n                   show the features' behavior for individual pieces and\n                   discuss their musical meaning. On the basis of these novel\n                   types of audio features, we perform comprehensive\n                   experiments for analyzing and classifying audio recordings\n                   regarding musical style. For this purpose, we apply\n                   methods from the field of machine learning. Using\n                   unsupervised clustering methods, we investigate the\n                   similarity of musical works across composers and\n                   composition years. Even though the underlying feature\n                   representations may be imprecise and error-prone in some\n                   cases, we can observe interesting tendencies that may\n                   exhibit some musical meaning when analyzing large\n                   databases. For example, we observe an increase of tonal\n                   complexity during the 19th and 20th century on the basis\n                   of our features. As an essential contribution of this\n                   dissertation, we perform automatic classification\n                   experiments according to historical periods (“eras”)\n                   and composers. We compile two datasets, on which we test\n                   common classifiers using both our tonal features and\n                   standardized audio features. Despite the vagueness of the\n                   task and the complexity of the data, we obtain good\n                   results for the classification with respect to historical\n                   periods. This indicates that the tonal features proposed\n                   in this thesis seem to robustly capture some stylistic\n                   properties. In contrast, using standardized timbral\n                   features for classification often leads to overfitting to\n                   the training data resulting in worse performance.\n                   Comparing different types of tonal features revealed that\n                   features relating to interval types, tonal complexity, and\n                   chord progressions are useful for classifying audio\n                   recordings with respect to musical style. This seems to\n                   validate the hypothesis that tonal characteristics can be\n                   discriminative for style analysis and that we can measure\n                   such characteristics directly from audio recordings. In\n                   summary, the interplay between musicology and audio signal\n                   processing can be very promising. When applied to a\n                   specific example, we have to be careful with the results\n                   of computational methods, which, of course, cannot compete\n                   with the experienced judgement of a musicologist. For\n                   analyzing comprehensive corpora, however,\n                   computer-assisted techniques provide interesting\n                   opportunities to recognize fundamental trends and to\n                   verify hypotheses.},\n    doi          = {10.1016/j.anr.2016.04.002},\n    isbn         = {0278-4319},\n    issn         = {20937482},\n    keywords     = {depression,kidney diseases,meta-analysis,music analysis\n                   with computers,quality of life,self-management},\n    mendeley-tags= {music analysis with computers},\n    pmid         = {28057311},\n    school       = {Technische Universit{\\"{a}}t Ilmenau},\n    type         = {Ph.D. Dissertation},\n    url          = {https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00039054/ilm1-2017000293.pdf}\n}\n\n
\n
\n\n\n
\n With the tremendously growing impact of digital technology, the ways of accessing music crucially changed. Nowadays, streaming services, download platforms, and private archives provide a large amount of music recordings to listeners. As tools for organizing and browsing such collections, automatic methods have become important. In the area of Music Informa- tion Retrieval, researchers are developing algorithms for analyzing and comparing music data with respect to musical characteristics. One typical application scenario is the classification of music recordings according to categories such as musical genres. In this thesis, we approach such classification problems with the goal of discriminating subgenres within Western classical music. In particular, we focus on typical categories such as historical periods or individual composers. From a musicological point of view, this classi- fication problem relates to the question of musical style, which constitutes a rather ill-defined and abstract concept. Usually, musicologists analyze musical scores in a manual fashion in order to acquire knowledge about style and its determining factors. This thesis contributes with computational methods for realizing such analyses on comprehensive corpora of audio recordings. Though it is hard to extract explicit information such as note events from audio data, the computational analysis of audio recordings might bear great potential for musi- cological research. One reason for this is the limited availability of symbolic scores in high quality. The style analysis experiments presented in this thesis focus on the fields of harmony and tonality. In the first step, we use signal processing techniques for computing chroma representations of the audio data. These semantic “mid-level” representations capture the pitch class content of an audio recording in a robust way and, thus, constitute a suitable starting point for subsequent processing steps. From such chroma representations, we derive measures for quantitatively describing stylistic properties of the music. Since chroma features suppress timbral characteristics to a certain extent, we hope to achieve invariance to timbre and instrumentation for our analysis methods. Inspired by the characteristics of the chroma representations, we model in this thesis specific concepts from music theory and propose algorithms to measure the occurence of certain tonal structures in audio recordings. One of the proposed methods aims at estimating the global key of a piece by considering the particular role of the final chord. Another contribution of this thesis is an automatic method to visualize modulations regarding diatonic scales as well as scale types over the course of a piece. Furthermore, we propose novel techniques for estimating the presence of specific interval and chord types and for measuring more abstract notions such as tonal complexity. In first experiments, we show the features' behavior for individual pieces and discuss their musical meaning. On the basis of these novel types of audio features, we perform comprehensive experiments for analyzing and classifying audio recordings regarding musical style. For this purpose, we apply methods from the field of machine learning. Using unsupervised clustering methods, we investigate the similarity of musical works across composers and composition years. Even though the underlying feature representations may be imprecise and error-prone in some cases, we can observe interesting tendencies that may exhibit some musical meaning when analyzing large databases. For example, we observe an increase of tonal complexity during the 19th and 20th century on the basis of our features. As an essential contribution of this dissertation, we perform automatic classification experiments according to historical periods (“eras”) and composers. We compile two datasets, on which we test common classifiers using both our tonal features and standardized audio features. Despite the vagueness of the task and the complexity of the data, we obtain good results for the classification with respect to historical periods. This indicates that the tonal features proposed in this thesis seem to robustly capture some stylistic properties. In contrast, using standardized timbral features for classification often leads to overfitting to the training data resulting in worse performance. Comparing different types of tonal features revealed that features relating to interval types, tonal complexity, and chord progressions are useful for classifying audio recordings with respect to musical style. This seems to validate the hypothesis that tonal characteristics can be discriminative for style analysis and that we can measure such characteristics directly from audio recordings. In summary, the interplay between musicology and audio signal processing can be very promising. When applied to a specific example, we have to be careful with the results of computational methods, which, of course, cannot compete with the experienced judgement of a musicologist. For analyzing comprehensive corpora, however, computer-assisted techniques provide interesting opportunities to recognize fundamental trends and to verify hypotheses.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n The Yale-Classical Archives Corpus.\n \n \n \n \n\n\n \n White, C. W.; and Quinn, I.\n\n\n \n\n\n\n Empirical Musicology Review, 11(1): 50. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          white.ea2016-yale-classical,\n    author       = {White, Christopher William and Quinn, Ian},\n    year         = {2016},\n    title        = {The Yale-Classical Archives Corpus},\n    abstract     = {The Yale-Classical Archives Corpus (YCAC) contains\n                   harmonic and rhythmic information for a dataset of Western\n                   European Classical art music. This corpus is based on data\n                   from classicalarchives.com, a repository of thousands of\n                   user-generated MIDI representations of pieces from several\n                   periods of Western European music history. The YCAC makes\n                   available metadata for each MIDI file, as well as a list\n                   of pitch simultaneities ("salami slices") in the MIDI\n                   file. Metadata include the piece's composer, the\n                   composer's country of origin, date of composition, genre\n                   (e.g., symphony, piano sonata, nocturne, etc.),\n                   instrumentation, meter, and key. The processing step\n                   groups the file's pitches into vertical slices each time a\n                   pitch is added or subtracted from the texture, recording\n                   the slice's offset (measured in the number of quarter\n                   notes separating the event from the file's beginning),\n                   highest pitch, lowest pitch, prime form, scale-degrees in\n                   relation to the global key (as determined by experts), and\n                   local key information (as determined by a windowed\n                   key-profile analysis). The corpus contains 13,769 MIDI\n                   files by 571 composers yielding over 14,051,144 vertical\n                   slices. This paper outlines several properties of this\n                   corpus, along with a representative study using this\n                   dataset.},\n    doi          = {10.18061/emr.v11i1.4958},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {academic inquiry,allowing scholars to quantify,amounts\n                   of,as the fields of,c omputational analysis of,common\n                   practice,corpus analysis,evidence,experiment with such\n                   methods,historical trends and bolster,intuitive\n                   observations with large,large data sets has,machine\n                   learning,music,music theory and musicology,style,there\n                   arises a need,tonality,transformed many aspects of},\n    mendeley-tags= {music},\n    number       = {1},\n    pages        = {50},\n    url          = {http://emusicology.org/article/view/4958/4397},\n    volume       = {11}\n}\n\n
\n
\n\n\n
\n The Yale-Classical Archives Corpus (YCAC) contains harmonic and rhythmic information for a dataset of Western European Classical art music. This corpus is based on data from classicalarchives.com, a repository of thousands of user-generated MIDI representations of pieces from several periods of Western European music history. The YCAC makes available metadata for each MIDI file, as well as a list of pitch simultaneities (\"salami slices\") in the MIDI file. Metadata include the piece's composer, the composer's country of origin, date of composition, genre (e.g., symphony, piano sonata, nocturne, etc.), instrumentation, meter, and key. The processing step groups the file's pitches into vertical slices each time a pitch is added or subtracted from the texture, recording the slice's offset (measured in the number of quarter notes separating the event from the file's beginning), highest pitch, lowest pitch, prime form, scale-degrees in relation to the global key (as determined by experts), and local key information (as determined by a windowed key-profile analysis). The corpus contains 13,769 MIDI files by 571 composers yielding over 14,051,144 vertical slices. This paper outlines several properties of this corpus, along with a representative study using this dataset.\n
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\n \n\n \n \n \n \n \n \n Getting closer to the essence of music: The con espressione manifesto.\n \n \n \n \n\n\n \n Widmer, G.\n\n\n \n\n\n\n ACM Transactions on Intelligent Systems and Technology, 8(2): 1–14. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"GettingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          widmer2016-getting,\n    author       = {Widmer, Gerhard},\n    year         = {2016},\n    title        = {Getting closer to the essence of music: The con\n                   espressione manifesto},\n    abstract     = {This text offers a personal and very subjective view on\n                   the current situation of Music Information Research (MIR).\n                   Motivated by the desire to build systems with a somewhat\n                   deeper understanding of music than the ones we currently\n                   have, I try to sketch a number of challenges for the next\n                   decade of MIR research, grouped around six simple truths\n                   about music that are probably generally agreed on but\n                   often ignored in everyday research.},\n    archiveprefix= {arXiv},\n    arxivid      = {1611.09733},\n    doi          = {10.1145/2899004},\n    eprint       = {1611.09733},\n    issn         = {21576912},\n    journal      = {ACM Transactions on Intelligent Systems and Technology},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval},\n    number       = {2},\n    pages        = {1--14},\n    url          = {http://www.cp.jku.at/research/projects/ConEspressione/pubs/manifesto.pdf},\n    volume       = {8}\n}\n\n
\n
\n\n\n
\n This text offers a personal and very subjective view on the current situation of Music Information Research (MIR). Motivated by the desire to build systems with a somewhat deeper understanding of music than the ones we currently have, I try to sketch a number of challenges for the next decade of MIR research, grouped around six simple truths about music that are probably generally agreed on but often ignored in everyday research.\n
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\n  \n 2015\n \n \n (16)\n \n \n
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\n \n\n \n \n \n \n \n \n Data Mining.\n \n \n \n \n\n\n \n Aggarwal, C. C.\n\n\n \n\n\n\n Springer International Publishing, Cham, 2015.\n \n\n\n\n
\n\n\n\n \n \n \"DataPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             aggarwal2015-data,\n    author       = {Aggarwal, Charu C.},\n    year         = {2015},\n    title        = {Data Mining},\n    address      = {Cham},\n    doi          = {10.1007/978-3-319-14142-8},\n    isbn         = {978-3-319-14141-1},\n    keywords     = {computer},\n    mendeley-tags= {computer},\n    publisher    = {Springer International Publishing},\n    url          = {https://linkinghub.elsevier.com/retrieve/pii/030438358190152X\n                   http://link.springer.com/10.1007/978-3-319-14142-8}\n}\n\n
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\n \n\n \n \n \n \n \n \n Corpus Analysis Tools For Computational Hook Discovery.\n \n \n \n \n\n\n \n Balen, J. V.; Burgoyne, J. A.; Bountouridis, D.; Müllensiefen, D.; and Veltkamp, R. C.\n\n\n \n\n\n\n . October 2015.\n Publisher: Zenodo\n\n\n\n
\n\n\n\n \n \n \"CorpusPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          balen.ea2015-corpus,\n    author       = {Balen, Jan Van and Burgoyne, John Ashley and\n                   Bountouridis, Dimitrios and Müllensiefen, Daniel and\n                   Veltkamp, Remco C.},\n    year         = {2015},\n    title        = {Corpus {Analysis} {Tools} {For} {Computational} {Hook}\n                   {Discovery}.},\n    copyright    = {Creative Commons Attribution 4.0, Open Access},\n    url          = {https://zenodo.org/record/1415038},\n    doi          = {10.5281/ZENODO.1415038},\n    abstract     = {Compared to studies with symbolic music data, advances in\n                   music description from audio have overwhelmingly focused\n                   on ground truth reconstruction and maximizing prediction\n                   accuracy, with only a small fraction of studies using\n                   audio description to gain insight into musical data. We\n                   present a strategy for the corpus analysis of audio data\n                   that is optimized for interpretable results. The approach\n                   brings two previously unexplored concepts to the audio\n                   domain: audio bigram distributions, and the use of\n                   corpus-relative or “second-order” descriptors. To test\n                   the real-world applicability of our method, we present an\n                   experiment in which we model song recognition data\n                   collected in a widely-played music game. By using the\n                   proposed corpus analysis pipeline we are able to present a\n                   cognitively adequate analysis that allows a model\n                   interpretation in terms of the listening history and\n                   experience of our participants. We find that our\n                   corpus-based audio features are able to explain a\n                   comparable amount of variance to symbolic features for\n                   this task when used alone and that they can supplement\n                   symbolic features profitably when the two types of\n                   features are used in tandem. Finally, we highlight new\n                   insights into what makes music recognizable.},\n    language     = {en},\n    urldate      = {2023-02-23},\n    month        = oct,\n    note         = {Publisher: Zenodo}\n}\n\n
\n
\n\n\n
\n Compared to studies with symbolic music data, advances in music description from audio have overwhelmingly focused on ground truth reconstruction and maximizing prediction accuracy, with only a small fraction of studies using audio description to gain insight into musical data. We present a strategy for the corpus analysis of audio data that is optimized for interpretable results. The approach brings two previously unexplored concepts to the audio domain: audio bigram distributions, and the use of corpus-relative or “second-order” descriptors. To test the real-world applicability of our method, we present an experiment in which we model song recognition data collected in a widely-played music game. By using the proposed corpus analysis pipeline we are able to present a cognitively adequate analysis that allows a model interpretation in terms of the listening history and experience of our participants. We find that our corpus-based audio features are able to explain a comparable amount of variance to symbolic features for this task when used alone and that they can supplement symbolic features profitably when the two types of features are used in tandem. Finally, we highlight new insights into what makes music recognizable.\n
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\n \n\n \n \n \n \n \n Evaluating automated classification techniques for folk music genres from the Brazilian Northeast.\n \n \n \n\n\n \n Barbosa, J.; Mckay, C.; and Fujinaga, I.\n\n\n \n\n\n\n Proceedings of the 15th Brazilian Symposium on Computer Music,3–12. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          barbosa.ea2015-evaluating,\n    author       = {Barbosa, Jeronimo and Mckay, Cory and Fujinaga, Ichiro},\n    year         = {2015},\n    title        = {Evaluating automated classification techniques for folk\n                   music genres from the Brazilian Northeast},\n    journal      = {Proceedings of the 15th Brazilian Symposium on Computer\n                   Music},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {3--12}\n}\n\n
\n
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\n \n\n \n \n \n \n \n Haydn's dramatic dissonances: chromaticism and formal process in his string quartets, opp. 9 and 17.\n \n \n \n\n\n \n Birson, A. M.\n\n\n \n\n\n\n Ph.D. Thesis, Cornell University, 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        birson2015-haydns,\n    author       = {Birson, Adem Merter},\n    year         = {2015},\n    title        = {Haydn's dramatic dissonances: chromaticism and formal\n                   process in his string quartets, opp. 9 and 17},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    school       = {Cornell University},\n    type         = {Ph.D. Dissertation}\n}\n\n
\n
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\n \n\n \n \n \n \n \n \n Theme and variation encodings with roman numerals (TaVERn): A new data set for symbolic music analysis.\n \n \n \n \n\n\n \n Devaney, J.; Arthur, C.; Condit-Schultz, N.; and Nisula, K.\n\n\n \n\n\n\n In Proceedings of the 16th International Society for Music Information Retrieval Conference, ISMIR 2015, pages 728–734, Málaga, Spain, 2015. International Society for Music Information Retrieval\n \n\n\n\n
\n\n\n\n \n \n \"ThemePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    devaney.ea2015-theme,\n    author       = {Devaney, Johanna and Arthur, Claire and Condit-Schultz,\n                   Nathaniel and Nisula, Kirsten},\n    year         = {2015},\n    title        = {Theme and variation encodings with roman numerals\n                   (TaVERn): A new data set for symbolic music analysis},\n    abstract     = {The Theme And Variation Encodings with Roman Numerals\n                   (TAVERN) dataset consists of 27 complete sets of theme and\n                   variations for piano composed between 1765 and 1810 by\n                   Mozart and Beethoven. In these theme and variation sets,\n                   comparable harmonic structures are realized in different\n                   ways. This facilitates an evaluation of the effectiveness\n                   of automatic analysis algorithms in generalizing across\n                   different musical textures. The pieces are encoded in\n                   standard **kern format, with analyses jointly encoded\n                   using an extension to **kern. The harmonic content of the\n                   music was analyzed with both Roman numerals and function\n                   labels in duplicate by two different expert analyzers. The\n                   pieces are divided into musical phrases, allowing for\n                   multiple-levels of automatic analysis, including chord\n                   labeling and phrase parsing. This paper describes the\n                   content of the dataset in detail, including the types of\n                   chords represented, and discusses the ways in which the\n                   analyzers sometimes disagreed on the lower-level harmonic\n                   content (the Roman numerals) while converging at similar\n                   high-level structures (the function of the chords within\n                   the phrase).},\n    address      = {M{\\'{a}}laga, Spain},\n    booktitle    = {Proceedings of the 16th International Society for Music\n                   Information Retrieval Conference, ISMIR 2015},\n    isbn         = {9788460688532},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {728--734},\n    publisher    = {International Society for Music Information Retrieval},\n    url          = {http://ismir2015.uma.es/articles/261_Paper.pdf}\n}\n\n
\n
\n\n\n
\n The Theme And Variation Encodings with Roman Numerals (TAVERN) dataset consists of 27 complete sets of theme and variations for piano composed between 1765 and 1810 by Mozart and Beethoven. In these theme and variation sets, comparable harmonic structures are realized in different ways. This facilitates an evaluation of the effectiveness of automatic analysis algorithms in generalizing across different musical textures. The pieces are encoded in standard **kern format, with analyses jointly encoded using an extension to **kern. The harmonic content of the music was analyzed with both Roman numerals and function labels in duplicate by two different expert analyzers. The pieces are divided into musical phrases, allowing for multiple-levels of automatic analysis, including chord labeling and phrase parsing. This paper describes the content of the dataset in detail, including the types of chords represented, and discusses the ways in which the analyzers sometimes disagreed on the lower-level harmonic content (the Roman numerals) while converging at similar high-level structures (the function of the chords within the phrase).\n
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\n \n\n \n \n \n \n \n \n Is it the song and not the singer? Hit song prediction using structural features of melodies.\n \n \n \n \n\n\n \n Frieler, K.; Jakubowski, K.; and Mullensiefen, D.\n\n\n \n\n\n\n Musikpsychologie Bd., 25: 41–54. 2015.\n \n\n\n\n
\n\n\n\n \n \n \"IsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          frieler.ea2015-is,\n    author       = {Frieler, Klaus and Jakubowski, Kelly and Mullensiefen,\n                   Daniel},\n    year         = {2015},\n    title        = {Is it the song and not the singer? Hit song prediction\n                   using structural features of melodies},\n    journal      = {Musikpsychologie Bd.},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {41--54},\n    url          = {https://www.researchgate.net/publication/281826659_Is_it_the_Song_and_Not_the_Singer_Hit_Song_Prediction_Using_Structural_Features_of_Melodies},\n    volume       = {25}\n}\n\n
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\n \n\n \n \n \n \n \n \n Análise formal de estruturas rítmicas de Meyer em diagrama de Hasse.\n \n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n In volume 2 - Processos criativos, pages 153–169, 2015. \n \n\n\n\n
\n\n\n\n \n \n \"AnálisePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@InProceedings{    gentil-nunes2015-analise,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2015},\n    title        = {An\\'{a}lise formal de estruturas r\\'{i}tmicas de {Meyer}\n                   em diagrama de {Hasse}},\n    volume       = {2 - Processos criativos},\n    url          = {14º Col\\'{o}quio de Pesquisa do PPGM/UFRJ},\n    abstract     = {O presente trabalho é parte de uma pesquisa mais ampla,\n                   desenvolvida no âmbito do Programa de P\\'{o}s-Graduação\n                   em Música da UFRJ – Grupo MusMat e consiste na\n                   formalização do conjunto de estruturas r\\'{i}tmicas\n                   propostas por Leonard Meyer (1960), baseadas na\n                   pros\\'{o}dia musical, resultando em sua taxonomia\n                   exaustiva e na definição de relações entre elementos\n                   (perfis r\\'{i}tmicos). Repercussões e cr\\'{i}ticas do\n                   trabalho de Meyer são revisadas e avaliadas. São\n                   apresentadas também pequenas an\\'{a}lises, como exemplos\n                   de aplicação elementar da formalização proposta.},\n    language     = {pt},\n    keywords     = {An\\'{a}lise Musical;, An\\'{a}lise Particional,\n                   Composição Musical, Reticulado de Young},\n    pages        = {153--169}\n}\n\n
\n
\n\n\n
\n O presente trabalho é parte de uma pesquisa mais ampla, desenvolvida no âmbito do Programa de Pós-Graduação em Música da UFRJ – Grupo MusMat e consiste na formalização do conjunto de estruturas rítmicas propostas por Leonard Meyer (1960), baseadas na prosódia musical, resultando em sua taxonomia exaustiva e na definição de relações entre elementos (perfis rítmicos). Repercussões e críticas do trabalho de Meyer são revisadas e avaliadas. São apresentadas também pequenas análises, como exemplos de aplicação elementar da formalização proposta.\n
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\n \n\n \n \n \n \n \n Corpus-based rhythmic pattern analysis of ragtime syncopation.\n \n \n \n\n\n \n Koops, H. V.; Volk, A.; and Bas de Haas, W.\n\n\n \n\n\n\n In Proceedings of the 16th International Society for Music Information Retrieval Conference, ISMIR 2015, pages 483–489, Malaga, Spain, 2015. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    koops.ea2015-corpus-based,\n    author       = {Koops, Hendrik Vincent and Volk, Anja and {Bas de Haas},\n                   W.},\n    year         = {2015},\n    title        = {Corpus-based rhythmic pattern analysis of ragtime\n                   syncopation},\n    abstract     = {This paper presents a corpus-based study on rhythmic\n                   patterns in the RAG-collection of approximately 11.000\n                   symbolically encoded ragtime pieces. While characteristic\n                   musical features that define ragtime as a genre have been\n                   debated since its inception, musicologists argue that\n                   specific syncopation patterns are most typical for this\n                   genre. Therefore, we investigate the use of syncopation\n                   patterns in the RAG-collection from its beginnings until\n                   the present time in this paper. Using computational\n                   methods, this paper provides an overview on the use of\n                   rhythmical patterns of the ragtime genre, thereby offering\n                   valuable new insights that complement musicological\n                   hypotheses about this genre. Specifically, we measure the\n                   amount of syncopation for each bar using Longuet-Higgins\n                   and Lee's model of syncopation, determine the most\n                   frequent rhythmic patterns, and discuss the role of a\n                   specific short-long-short syncopation pattern that\n                   musicologists argue is characteristic for ragtime. A\n                   comparison between the ragtime (pre-1920) and modern\n                   (post-1920) era shows that the two eras differ in\n                   syncopation pattern use. Onset density and amount of\n                   syncopation increase after 1920. Moreover, our study\n                   confirms the musicological hypothesis on the important\n                   role of the short-long-short syncopation pattern in\n                   ragtime. These findings are pivotal in developing ragtime\n                   genre-specific features.},\n    address      = {Malaga, Spain},\n    booktitle    = {Proceedings of the 16th International Society for Music\n                   Information Retrieval Conference, ISMIR 2015},\n    isbn         = {9788460688532},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval},\n    pages        = {483--489}\n}\n\n
\n
\n\n\n
\n This paper presents a corpus-based study on rhythmic patterns in the RAG-collection of approximately 11.000 symbolically encoded ragtime pieces. While characteristic musical features that define ragtime as a genre have been debated since its inception, musicologists argue that specific syncopation patterns are most typical for this genre. Therefore, we investigate the use of syncopation patterns in the RAG-collection from its beginnings until the present time in this paper. Using computational methods, this paper provides an overview on the use of rhythmical patterns of the ragtime genre, thereby offering valuable new insights that complement musicological hypotheses about this genre. Specifically, we measure the amount of syncopation for each bar using Longuet-Higgins and Lee's model of syncopation, determine the most frequent rhythmic patterns, and discuss the role of a specific short-long-short syncopation pattern that musicologists argue is characteristic for ragtime. A comparison between the ragtime (pre-1920) and modern (post-1920) era shows that the two eras differ in syncopation pattern use. Onset density and amount of syncopation increase after 1920. Moreover, our study confirms the musicological hypothesis on the important role of the short-long-short syncopation pattern in ragtime. These findings are pivotal in developing ragtime genre-specific features.\n
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\n \n\n \n \n \n \n \n \n Normative wit: Haydn's personal Sonata Form.\n \n \n \n \n\n\n \n Mastic, T. R.\n\n\n \n\n\n\n Ph.D. Thesis, University of Oregon, 2015.\n \n\n\n\n
\n\n\n\n \n \n \"NormativePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        mastic2015-normative,\n    author       = {Mastic, Timothy R.},\n    year         = {2015},\n    title        = {Normative wit: Haydn's personal Sonata Form},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    school       = {University of Oregon},\n    type         = {Master Thesis},\n    url          = {https://www.academia.edu/10763858/Normative_Wit_Haydns_Personal_Sonata_Form}\n}\n\n
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\n \n\n \n \n \n \n \n Computational Music Analysis.\n \n \n \n\n\n \n Meredith, D.,\n editor.\n \n\n\n \n\n\n\n Springer, New York, 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             meredith2015-computational,\n    year         = {2015},\n    title        = {Computational Music Analysis},\n    address      = {New York},\n    editor       = {Meredith, David},\n    isbn         = {9783319259291},\n    keywords     = {music similarity},\n    mendeley-tags= {music similarity},\n    publisher    = {Springer}\n}\n\n
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\n \n\n \n \n \n \n \n A computational analysis study of children's songs from different countries.\n \n \n \n\n\n \n Papasarantopoulos, N.; Poulakis, N.; and Anagnostopoulou, C.\n\n\n \n\n\n\n In Ginsborg, J.; Lamont, A.; Phillips, M.; and Bramley, S., editor(s), Proceedings of the Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, pages 626–630, Manchester, UK, 2015. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    papasarantopoulos.ea2015-computational,\n    author       = {Papasarantopoulos, Nikos and Poulakis, Nick and\n                   Anagnostopoulou, Christina},\n    year         = {2015},\n    title        = {A computational analysis study of children's songs from\n                   different countries},\n    address      = {Manchester, UK},\n    booktitle    = {Proceedings of the Ninth Triennial Conference of the\n                   European Society for the Cognitive Sciences of Music},\n    editor       = {Ginsborg, J. and Lamont, A. and Phillips, M. and Bramley,\n                   S.},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {626--630}\n}\n\n
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\n \n\n \n \n \n \n \n The Challenge of Data in Digital Musicology.\n \n \n \n\n\n \n Pugin, L.\n\n\n \n\n\n\n Frontiers in Digital Humanities, 2(August): 19–21. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          pugin2015-challenge,\n    author       = {Pugin, Laurent},\n    year         = {2015},\n    title        = {The Challenge of Data in Digital Musicology},\n    abstract     = {Most of our work in the humanities is increasingly driven\n                   by digital technology. Musicology is no exception and the\n                   field is undergoing the same revolution as all disciplines\n                   in the humanities. There are at least two key areas in\n                   which digital technology is transforming research: access\n                   and scale. Technology, and the internet in particular, has\n                   radically changed how we can access data, but also how we\n                   can make research results accessible to others.\n                   Correlatively, the scope of projects can be broadened to a\n                   completely new extent. What does this mean for musicology?\n                   Scholars in musicology base their work on a wide range of\n                   materials. Since most of the music that forms our heritage\n                   in Western culture has been preserved in a text-based\n                   form, this is by far, the most widely used type of\n                   material for musicological studies. Handwritten and\n                   printed sources constitute the core data, but historical\n                   studies also rely on various types of textual and archival\n                   material, be they letter writings, libretti, or\n                   inventories of diverse kind. These are essential for\n                   understanding the socio-economic context in which the\n                   music sources were written or produced and for better\n                   understanding of specific aspects, such as performance\n                   practice of the time. Performance practice study itself\n                   may also be based on sound recordings when focusing on\n                   relatively recent history, as it is often the case for\n                   studies in ethno-musicology or in folk-songs (Cook, 2010).\n                   Obtaining access to the sources has always been a struggle\n                   for musicologists. Only a few years ago, studying a\n                   particular source meant first locating the relevant\n                   sources using printed bibliographies, writing to the\n                   holding library, and then waiting for a microfilm to be\n                   prepared and sent out. The process could take months and\n                   be unpredictably expensive, with no guarantee of success.\n                   Such an obstacle seriously reduced the breadth of research\n                   musicologists could reasonably envisage, with a consequent\n                   inclination toward close-reading approaches on a\n                   restricted set of sources. With the coming of the digital\n                   world, the situation changed. Many resources are now\n                   available online, including the bibliographic finding\n                   aids, which makes locating sources significantly easier.\n                   Collections are being digitized and made accessible\n                   online, which greatly facilitates access to them for\n                   musicologists. This is also the case for secondary\n                   sources. Some projects are composer-specific, such as the\n                   Digital Archive of the Beethoven-Haus, others are\n                   repertoire-oriented, such as the digital image archive for\n                   medieval manuscripts (DIAMM) or based on a particular\n                   library collection, such as the Julliard Manuscript\n                   Collection, to cite only three examples. In the archives,\n                   digital cameras are often allowed and can be used to\n                   capture sources quickly. It is now straightforward for\n                   scholars to store thousands of images on their personal\n                   computer, in the cloud, or even share them on community\n                   websites, although this in its turn raises new copyright\n                   concerns. What other issues need to be addressed? Digital\n                   access in musicology is still overwhelmingly linked to\n                   images. Several important digital musicology research\n                   projects, such as the OCVE and the Edirom projects,\n                   focusing mostly on philological issues have been very\n                   successful in relying extensively on digital image\n                   resources (Bradley and Vetch, 2007; Bohl et al., 2011).\n                   However, digital musicology projects that address a wide\n                   range of other issues, such as music analysis or music\n                   searching, require access to the music itself in digital\n                   form, are referred to as content-based resources.\n                   Musicology has never been behind other disciplines for\n                   experimenting with computational approaches in these\n                   domains, quite on the Frontiers in Digital Humanities |\n                   www.frontiersin.org August 2015 | Volume 2 | Article 4 1\n                   Pugin Data in digital musicology contrary. However,\n                   obtaining or accessing high quality datasets remains a\n                   serious hurdle, especially on a large scale, in a similar\n                   way to accessing sources a couple of decades ago. It is a\n                   major barrier that needs to be removed if digital\n                   musicology research is to be taken to the next level.\n                   Several initiatives have laid down the basis for\n                   large-scale content-based resources. First and foremost,\n                   the CCARH with its KernScores repository 1 , which\n                   represents years of careful data creation and curation is\n                   made available for research and is an invaluable\n                   contribution. The Josquin Research Project (JRP 2) at\n                   Stanford is a groundbreaking project that is currently\n                   building a considerable dataset of pieces of Josquin des\n                   Prez and of other composers of the time (1400–1500).\n                   Another is the Electronic Locator of Vertical Interval\n                   Successions project at McGill Uni-versity (ELVIS 3). These\n                   two projects pursue similar goals and follow more or less\n                   comparable strategies: respectively creating or collecting\n                   a large collection of data and making it accessi-ble and\n                   analyzable by integrating state-of-the-art analysis tools\n                   Humdrum and Music21. Their output in terms of counterpoint\n                   analysis is a breakthrough and opens new perspectives for\n                   style analysis and composition attribution. The use of the\n                   harmonic and melodic intervals in ELVIS illuminates areas\n                   in which inno-vative research might be needed to address\n                   the question of how to represent music appropriately for\n                   such corpus-based analysis undertakings. These are\n                   undoubtedly models to follow, but they also illustrate how\n                   much still needs to be done. They hold a few thousand\n                   pieces 4},\n    doi          = {10.3389/fdigh.2015.00004},\n    issn         = {2297-2668},\n    journal      = {Frontiers in Digital Humanities},\n    keywords     = {ccarh,content-based music resources,digital\n                   musicology,edited and reviewed by,eleanor\n                   selfridge-field,music analysis,music\n                   encoding,musicology,the packard,usa},\n    mendeley-tags= {musicology},\n    number       = {August},\n    pages        = {19--21},\n    volume       = {2}\n}\n\n
\n
\n\n\n
\n Most of our work in the humanities is increasingly driven by digital technology. Musicology is no exception and the field is undergoing the same revolution as all disciplines in the humanities. There are at least two key areas in which digital technology is transforming research: access and scale. Technology, and the internet in particular, has radically changed how we can access data, but also how we can make research results accessible to others. Correlatively, the scope of projects can be broadened to a completely new extent. What does this mean for musicology? Scholars in musicology base their work on a wide range of materials. Since most of the music that forms our heritage in Western culture has been preserved in a text-based form, this is by far, the most widely used type of material for musicological studies. Handwritten and printed sources constitute the core data, but historical studies also rely on various types of textual and archival material, be they letter writings, libretti, or inventories of diverse kind. These are essential for understanding the socio-economic context in which the music sources were written or produced and for better understanding of specific aspects, such as performance practice of the time. Performance practice study itself may also be based on sound recordings when focusing on relatively recent history, as it is often the case for studies in ethno-musicology or in folk-songs (Cook, 2010). Obtaining access to the sources has always been a struggle for musicologists. Only a few years ago, studying a particular source meant first locating the relevant sources using printed bibliographies, writing to the holding library, and then waiting for a microfilm to be prepared and sent out. The process could take months and be unpredictably expensive, with no guarantee of success. Such an obstacle seriously reduced the breadth of research musicologists could reasonably envisage, with a consequent inclination toward close-reading approaches on a restricted set of sources. With the coming of the digital world, the situation changed. Many resources are now available online, including the bibliographic finding aids, which makes locating sources significantly easier. Collections are being digitized and made accessible online, which greatly facilitates access to them for musicologists. This is also the case for secondary sources. Some projects are composer-specific, such as the Digital Archive of the Beethoven-Haus, others are repertoire-oriented, such as the digital image archive for medieval manuscripts (DIAMM) or based on a particular library collection, such as the Julliard Manuscript Collection, to cite only three examples. In the archives, digital cameras are often allowed and can be used to capture sources quickly. It is now straightforward for scholars to store thousands of images on their personal computer, in the cloud, or even share them on community websites, although this in its turn raises new copyright concerns. What other issues need to be addressed? Digital access in musicology is still overwhelmingly linked to images. Several important digital musicology research projects, such as the OCVE and the Edirom projects, focusing mostly on philological issues have been very successful in relying extensively on digital image resources (Bradley and Vetch, 2007; Bohl et al., 2011). However, digital musicology projects that address a wide range of other issues, such as music analysis or music searching, require access to the music itself in digital form, are referred to as content-based resources. Musicology has never been behind other disciplines for experimenting with computational approaches in these domains, quite on the Frontiers in Digital Humanities | www.frontiersin.org August 2015 | Volume 2 | Article 4 1 Pugin Data in digital musicology contrary. However, obtaining or accessing high quality datasets remains a serious hurdle, especially on a large scale, in a similar way to accessing sources a couple of decades ago. It is a major barrier that needs to be removed if digital musicology research is to be taken to the next level. Several initiatives have laid down the basis for large-scale content-based resources. First and foremost, the CCARH with its KernScores repository 1 , which represents years of careful data creation and curation is made available for research and is an invaluable contribution. The Josquin Research Project (JRP 2) at Stanford is a groundbreaking project that is currently building a considerable dataset of pieces of Josquin des Prez and of other composers of the time (1400–1500). Another is the Electronic Locator of Vertical Interval Successions project at McGill Uni-versity (ELVIS 3). These two projects pursue similar goals and follow more or less comparable strategies: respectively creating or collecting a large collection of data and making it accessi-ble and analyzable by integrating state-of-the-art analysis tools Humdrum and Music21. Their output in terms of counterpoint analysis is a breakthrough and opens new perspectives for style analysis and composition attribution. The use of the harmonic and melodic intervals in ELVIS illuminates areas in which inno-vative research might be needed to address the question of how to represent music appropriately for such corpus-based analysis undertakings. These are undoubtedly models to follow, but they also illustrate how much still needs to be done. They hold a few thousand pieces 4\n
\n\n\n
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\n \n\n \n \n \n \n \n The sonata principle reformulated for Haydn post-1770 and a typology of his recapitulatory strategies.\n \n \n \n\n\n \n Riley, M.\n\n\n \n\n\n\n Journal of the Royal Musical Association, 140(1): 1–39. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          riley2015-sonata,\n    author       = {Riley, Matthew},\n    year         = {2015},\n    title        = {The sonata principle reformulated for Haydn post-1770 and\n                   a typology of his recapitulatory strategies},\n    doi          = {10.1080/02690403.2015.1008862},\n    issn         = {02690403},\n    journal      = {Journal of the Royal Musical Association},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {1--39},\n    volume       = {140}\n}\n\n
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\n \n\n \n \n \n \n \n \n Another lesson from Lassus: Using computers to analyse counterpoint.\n \n \n \n \n\n\n \n Schubert, P.; and Cumming, J.\n\n\n \n\n\n\n Early Music, 43(4): 577–586. 2015.\n \n\n\n\n
\n\n\n\n \n \n \"AnotherPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          schubert.ea2015-another,\n    author       = {Schubert, Peter and Cumming, Julie},\n    year         = {2015},\n    title        = {Another lesson from Lassus: Using computers to analyse\n                   counterpoint},\n    abstract     = {The authors report on experiments they have run using the\n                   computer to search a small corpus of Renaissance pieces\n                   (the famous Lassus duos of 1577) for recurring\n                   contrapuntal combinations. They liken these combinations\n                   (or 'modules' as Jessie Ann Owens has called them) to\n                   words in a text, and the process of finding them, to work\n                   done by linguists such as John Sinclair on large corpora\n                   of text. The program used was devised by a team at McGill\n                   University as part of the ELVIS ('Electronic Locator of\n                   Vertical Interval Successions') project. The interval\n                   successions are identified by the vertical intervals and\n                   the melodic motions that connect them, in the manner of\n                   Tinctoris's counterpoint treatise (1477), which\n                   illustrates most of the possible ways two vertical\n                   intervals can be connected. The authors find that some\n                   short interval successions appear, as we would expect, in\n                   repetitions of thematic material (i.e. as parts of\n                   soggetti associated with specific text phrases). Others,\n                   however, occur in apparently run-of-the-mill counterpoint:\n                   in the middle of words, in the middle of melismas, across\n                   phrase boundaries and embellished in a variety of ways.\n                   These often exhibit surprising consistency as to semitone\n                   position and possible modal associations. [ABSTRACT FROM\n                   AUTHOR]},\n    doi          = {10.1093/em/cav088},\n    issn         = {03061078},\n    journal      = {Early Music},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {4},\n    pages        = {577--586},\n    url          = {https://www.academia.edu/20226339/Another_Lesson_from_Lassus_Using_Computers_to_Analyze_Counterpoint},\n    volume       = {43}\n}\n\n
\n
\n\n\n
\n The authors report on experiments they have run using the computer to search a small corpus of Renaissance pieces (the famous Lassus duos of 1577) for recurring contrapuntal combinations. They liken these combinations (or 'modules' as Jessie Ann Owens has called them) to words in a text, and the process of finding them, to work done by linguists such as John Sinclair on large corpora of text. The program used was devised by a team at McGill University as part of the ELVIS ('Electronic Locator of Vertical Interval Successions') project. The interval successions are identified by the vertical intervals and the melodic motions that connect them, in the manner of Tinctoris's counterpoint treatise (1477), which illustrates most of the possible ways two vertical intervals can be connected. The authors find that some short interval successions appear, as we would expect, in repetitions of thematic material (i.e. as parts of soggetti associated with specific text phrases). Others, however, occur in apparently run-of-the-mill counterpoint: in the middle of words, in the middle of melismas, across phrase boundaries and embellished in a variety of ways. These often exhibit surprising consistency as to semitone position and possible modal associations. [ABSTRACT FROM AUTHOR]\n
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\n \n\n \n \n \n \n \n \n Perspectivas para a análise textural a partir da mediação entre a Teoria dos Contornos e a Análise Particional.\n \n \n \n \n\n\n \n de Sousa, D. M.\n\n\n \n\n\n\n Ph.D. Thesis, Universidade Federal do Rio de Janeiro, 2015.\n \n\n\n\n
\n\n\n\n \n \n \"PerspectivasPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@PhDThesis{        sousa2015-perspectivas,\n    author       = {de Sousa, Daniel Moreira},\n    year         = {2015},\n    title        = {Perspectivas para a an{\\'{a}}lise textural a partir da\n                   media{\\c{c}}{\\~{a}}o entre a Teoria dos Contornos e a\n                   An{\\'{a}}lise Particional},\n    abstract     = {O Contorno Textural é uma proposta original que surge a\n                   partir de uma nova aplicação da Teoria dos Contornos\n                   Musicais, desenvolvida principalmente por Friedmann\n                   (1985), Morris (1987) e Marvin e Laprade (1987), no campo\n                   textural, através da utilização de alguns conceitos\n                   da Análise Particional (GENTIL-NUNES e CARVALHO, 2003). O\n                   principal objetivo do Contorno Textural é permitir a\n                   realização de um estudo aprofundado das progressões\n                   texturais através da observação de uma curva de\n                   complexidade textural, constituída a partir da\n                   aplicação do conceito de abstração de níveis da\n                   Teoria dos Contornos na organização hierárquica das\n                   configurações texturais. São destacadas algumas\n                   ferramentas conceituais tanto da Teoria dos Contornos\n                   quanto da Análise Particional utilizadas na\n                   formulação do Contorno Textural. Um conjunto de\n                   ferramentas e conceitos originais elaborados durante a\n                   pesquisa são demonstrados em pequenos exemplos de\n                   diferentes compositores. A abordagem analítica é\n                   explorada na análise da Introdução da Sagração da\n                   Primavera de Igor Stravinsky (1913/1989) e do Prélude\n                   à L'après-midi d'un faune de Claude Debussy\n                   (1892/1981), considerando também possíveis relações\n                   entre a textura e o contorno melódico de seus\n                   respectivos temas iniciais. A aplicação em processo\n                   criativo foi realizada na obra Skyline para vibrafone\n                   solo, cujo as escolhas texturais, assim como a\n                   definição de outros parâmetros como o espaço de\n                   alturas, o ritmo e o andamento, foram norteadas pela\n                   escolha prévia de um contorno. Três aplicativos\n                   computacionais foram desenvolvidos para facilitar a\n                   implementação da presente proposta e suas\n                   características e funções são detalhadas:\n                   Operadores Particionais (GENTIL-NUNES; MOREIRA, 2013),\n                   Contour Analyzer (MOREIRA, 2014c) e Jacquard (MOREIRA,\n                   2015b).},\n    keywords     = {Análise Musical,Análise\n                   Particional,Composição,Progressão Textural,Teoria\n                   dos Contornos,music contour},\n    mendeley-tags= {music contour},\n    school       = {Universidade Federal do Rio de Janeiro},\n    type         = {Disserta{\\c{c}}{\\~{a}}o de mestrado},\n    url          = {https://www.dropbox.com/s/7ak966u7k7rt4x0/Perspectivas\n                   para a an{\\'{a}}lise textural a partir da\n                   media{\\c{c}}{\\~{a}}o entre a Teoria dos Contornos e a\n                   An{\\'{a}}lise Particional %28Daniel Moreira%29.pdf?dl=0\n                   https://www.academia.edu/14877490/Perspectivas_para_a_an{\\'{a}}lise_textural_a}\n}\n\n
\n
\n\n\n
\n O Contorno Textural é uma proposta original que surge a partir de uma nova aplicação da Teoria dos Contornos Musicais, desenvolvida principalmente por Friedmann (1985), Morris (1987) e Marvin e Laprade (1987), no campo textural, através da utilização de alguns conceitos da Análise Particional (GENTIL-NUNES e CARVALHO, 2003). O principal objetivo do Contorno Textural é permitir a realização de um estudo aprofundado das progressões texturais através da observação de uma curva de complexidade textural, constituída a partir da aplicação do conceito de abstração de níveis da Teoria dos Contornos na organização hierárquica das configurações texturais. São destacadas algumas ferramentas conceituais tanto da Teoria dos Contornos quanto da Análise Particional utilizadas na formulação do Contorno Textural. Um conjunto de ferramentas e conceitos originais elaborados durante a pesquisa são demonstrados em pequenos exemplos de diferentes compositores. A abordagem analítica é explorada na análise da Introdução da Sagração da Primavera de Igor Stravinsky (1913/1989) e do Prélude à L'après-midi d'un faune de Claude Debussy (1892/1981), considerando também possíveis relações entre a textura e o contorno melódico de seus respectivos temas iniciais. A aplicação em processo criativo foi realizada na obra Skyline para vibrafone solo, cujo as escolhas texturais, assim como a definição de outros parâmetros como o espaço de alturas, o ritmo e o andamento, foram norteadas pela escolha prévia de um contorno. Três aplicativos computacionais foram desenvolvidos para facilitar a implementação da presente proposta e suas características e funções são detalhadas: Operadores Particionais (GENTIL-NUNES; MOREIRA, 2013), Contour Analyzer (MOREIRA, 2014c) e Jacquard (MOREIRA, 2015b).\n
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\n \n\n \n \n \n \n \n Tonal complexity features for style classification of classical music.\n \n \n \n\n\n \n Weiß, C.; and Muller, M.\n\n\n \n\n\n\n In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pages 688–692, 2015. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    wei.ea2015-tonal,\n    author       = {Wei{\\ss}, Christof and Muller, Meinard},\n    year         = {2015},\n    title        = {Tonal complexity features for style classification of\n                   classical music},\n    abstract     = {We propose a set of novel audio features for classifying\n                   the style of classical music. The features rely on\n                   statistical measures based on a chroma feature\n                   representation of the audio data and describe the tonal\n                   complexity of the music, independently from the\n                   orchestration or timbre of the music. To analyze this\n                   property, we use a dataset containing piano and orchestral\n                   music from four general historical periods including\n                   Baroque, Classical, Romantic, and Modern. By applying\n                   dimensionality reduction techniques, we derive\n                   visualizations that demonstrate the discriminative power\n                   of the features with regard to the music styles. In\n                   classification experiments, we evaluate the features'\n                   performance using an SVM classifier. We investigate the\n                   influence of artist filtering with respect to the\n                   individual composers on the classification performance. In\n                   all experiments, we compare the results to the performance\n                   of standard features. We show that the introduced features\n                   capture meaningful properties of musical style and are\n                   robust to timbral variations. {\\textcopyright} 2015 IEEE.},\n    booktitle    = {ICASSP, IEEE International Conference on Acoustics,\n                   Speech and Signal Processing - Proceedings},\n    doi          = {10.1109/ICASSP.2015.7178057},\n    isbn         = {9781467369978},\n    issn         = {15206149},\n    keywords     = {Musical Style Classification,Tonal Features,music\n                   analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {June 2016},\n    pages        = {688--692}\n}\n\n
\n
\n\n\n
\n We propose a set of novel audio features for classifying the style of classical music. The features rely on statistical measures based on a chroma feature representation of the audio data and describe the tonal complexity of the music, independently from the orchestration or timbre of the music. To analyze this property, we use a dataset containing piano and orchestral music from four general historical periods including Baroque, Classical, Romantic, and Modern. By applying dimensionality reduction techniques, we derive visualizations that demonstrate the discriminative power of the features with regard to the music styles. In classification experiments, we evaluate the features' performance using an SVM classifier. We investigate the influence of artist filtering with respect to the individual composers on the classification performance. In all experiments, we compare the results to the performance of standard features. We show that the introduced features capture meaningful properties of musical style and are robust to timbral variations. © 2015 IEEE.\n
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\n  \n 2014\n \n \n (14)\n \n \n
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\n \n\n \n \n \n \n \n The Use of Minor Mode and Playing With Sonority in the Expositions of Haydn's String Quartets, Opp. 9 and 17.\n \n \n \n\n\n \n Birson, A. M.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 4(1): 1–30. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          birson2014-use,\n    author       = {Birson, Adem Merter},\n    year         = {2014},\n    title        = {The Use of Minor Mode and Playing With Sonority in the\n                   Expositions of Haydn's String Quartets, Opp. 9 and 17},\n    abstract     = {Haydn's early string quartets have been receiving more\n                   scholarly attention than previously within the last\n                   decade. Whether they treat these works as part of larger\n                   discussions of the entire ouvre of Haydn's quartets, or as\n                   the focus of studies in their own right, scholars have\n                   recently been willing to break from the traditional focus\n                   on quartets beginning from Op. 33 and allow for deeper\n                   engagement with the early quartets on terms more broadly\n                   conceived. This study aims to add to the growing body of\n                   knowledge on Opp. 9 and 17 by demonstrating how the first\n                   movements of Op. 9 no. 1 in C major, Op. 17 no. 2 in F\n                   major and Op. 17 no. 6 in D major each employ the minor\n                   mode at analogous moments in the exposition, with a\n                   disruptive effect on both the harmonic progression and the\n                   emotional register of the music. The impact of these modal\n                   digressions is analyzed, as they lead to climactic moments\n                   of fixation on a dissonant sonority. This momentarily\n                   freezes all four voices of the ensemble in a chromatic\n                   harmony that lends an expressive, at times even eccentric,\n                   character to the tonal drama. Thus important musical\n                   moments are uncovered, which have mostly gone unnoticed\n                   due to a general lack of emphasis of the early quartets as\n                   serious works. This approach opens up new avenues to\n                   understanding of the harmonic and expressive capability of\n                   Haydn's approach to sonata form.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {1--30},\n    volume       = {4}\n}\n\n
\n
\n\n\n
\n Haydn's early string quartets have been receiving more scholarly attention than previously within the last decade. Whether they treat these works as part of larger discussions of the entire ouvre of Haydn's quartets, or as the focus of studies in their own right, scholars have recently been willing to break from the traditional focus on quartets beginning from Op. 33 and allow for deeper engagement with the early quartets on terms more broadly conceived. This study aims to add to the growing body of knowledge on Opp. 9 and 17 by demonstrating how the first movements of Op. 9 no. 1 in C major, Op. 17 no. 2 in F major and Op. 17 no. 6 in D major each employ the minor mode at analogous moments in the exposition, with a disruptive effect on both the harmonic progression and the emotional register of the music. The impact of these modal digressions is analyzed, as they lead to climactic moments of fixation on a dissonant sonority. This momentarily freezes all four voices of the ensemble in a chromatic harmony that lends an expressive, at times even eccentric, character to the tonal drama. Thus important musical moments are uncovered, which have mostly gone unnoticed due to a general lack of emphasis of the early quartets as serious works. This approach opens up new avenues to understanding of the harmonic and expressive capability of Haydn's approach to sonata form.\n
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\n \n\n \n \n \n \n \n \n An Idiom-independent Representation of Chords for Computational Music Analysis and Generation.\n \n \n \n \n\n\n \n Cambouropoulos, E.; Kaliakatsos-Papakostas, M.; and Tsougras, C.\n\n\n \n\n\n\n In Proc. Joint 40th International Computer Music Conference (ICMC) and 11th Sound and Music Computing (SMC) Conference (ICMC- SMC2014), pages 1002–1009, Athens, Greece, 2014. \n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    cambouropoulos.ea2014-idiom-independent,\n    author       = {Cambouropoulos, Emilios and Kaliakatsos-Papakostas,\n                   Maximos and Tsougras, Costas},\n    year         = {2014},\n    title        = {An Idiom-independent Representation of Chords for\n                   Computational Music Analysis and Generation},\n    abstract     = {In this paper we focus on issues of harmonic representa-\n                   tion and computational analysis. A new idiom- independent\n                   representation is proposed of chord types that is\n                   appropriate for encoding tone simultaneities in any\n                   harmonic context (such as tonal, modal, jazz, octatonic,\n                   atonal). The General Chord Type (GCT) representation,\n                   allows the re-arrangement of the notes of a harmonic\n                   simultaneity such that abstract idiom-specific types of\n                   chords may be derived; this encoding is inspired by the\n                   standard roman numeral chord type labeling, but is more\n                   general and flexible. Given a consonance-dissonance\n                   classification of intervals (that reflects culturally-\n                   dependent notions of consonance/dissonance), and a scale,\n                   the GCT algorithm finds the maximal subset of notes of a\n                   given note simultaneity that contains only con- sonant\n                   intervals; this maximal subset forms the base upon which\n                   the chord type is built. The proposed representa- tion is\n                   ideal for hierarchic harmonic systems such as the tonal\n                   system and its many variations, but adjusts to any other\n                   harmonic system such as post-tonal, atonal music, or\n                   traditional polyphonic systems. The GCT representa- tion\n                   is applied to a small set of examples from diverse musical\n                   idioms, and its output is illustrated and analysed showing\n                   its potential, especially, for computational music\n                   analysis \\& music information retrieval.},\n    address      = {Athens, Greece},\n    booktitle    = {Proc. Joint 40th International Computer Music Conference\n                   (ICMC) and 11th Sound and Music Computing (SMC) Conference\n                   (ICMC- SMC2014)},\n    doi          = {10.13140/2.1.4128.1281},\n    isbn         = {9789604661374},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    number       = {September},\n    pages        = {1002--1009},\n    url          = {https://www.researchgate.net/profile/Emilios_Cambouropoulos/publication/266614715_An_Idiom-independent_Representation_of_Chords_for_Computational_Music_Analysis_and_Generation/links/54354b240cf2bf1f1f286e3e.pdf}\n}\n\n
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\n In this paper we focus on issues of harmonic representa- tion and computational analysis. A new idiom- independent representation is proposed of chord types that is appropriate for encoding tone simultaneities in any harmonic context (such as tonal, modal, jazz, octatonic, atonal). The General Chord Type (GCT) representation, allows the re-arrangement of the notes of a harmonic simultaneity such that abstract idiom-specific types of chords may be derived; this encoding is inspired by the standard roman numeral chord type labeling, but is more general and flexible. Given a consonance-dissonance classification of intervals (that reflects culturally- dependent notions of consonance/dissonance), and a scale, the GCT algorithm finds the maximal subset of notes of a given note simultaneity that contains only con- sonant intervals; this maximal subset forms the base upon which the chord type is built. The proposed representa- tion is ideal for hierarchic harmonic systems such as the tonal system and its many variations, but adjusts to any other harmonic system such as post-tonal, atonal music, or traditional polyphonic systems. The GCT representa- tion is applied to a small set of examples from diverse musical idioms, and its output is illustrated and analysed showing its potential, especially, for computational music analysis & music information retrieval.\n
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\n \n\n \n \n \n \n \n \n The Expositions of Haydn's String Quartets: A Corpus Analysis.\n \n \n \n \n\n\n \n Cortens, E.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 4(1). 2014.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          cortens2014-expositions,\n    author       = {Cortens, Evan},\n    year         = {2014},\n    title        = {The Expositions of Haydn's String Quartets: A Corpus\n                   Analysis},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    url          = {https://www.rit.edu/affiliate/haydn/expositions-haydn's-string-quartets-corpus-analysis},\n    volume       = {4}\n}\n\n
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\n \n\n \n \n \n \n \n \n Vers une analyse automatique des formes sonates.\n \n \n \n \n\n\n \n David, L.; Giraud, M.; Groult, R.; Levé, F.; and Louboutin, C.\n\n\n \n\n\n\n Journées d'Informatique Musicale (JIM 2014),113–118. 2014.\n \n\n\n\n
\n\n\n\n \n \n \"VersPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          david.ea2014-vers,\n    author       = {David, Laurent and Giraud, Mathieu and Groult, Richard\n                   and Lev{\\'{e}}, Florence and Louboutin, Corentin},\n    year         = {2014},\n    title        = {Vers une analyse automatique des formes sonates},\n    journal      = {Journ{\\'{e}}es d'Informatique Musicale (JIM 2014)},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {113--118},\n    url          = {https://hal.archives-ouvertes.fr/hal-01009166/document}\n}\n\n
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\n \n\n \n \n \n \n \n \n Statistical Analysis and Graphic Representation of the Correlation of Bach and Chopin Preludes.\n \n \n \n \n\n\n \n Donato, S. M\n\n\n \n\n\n\n Ph.D. Thesis, University of Vermont, 2014.\n \n\n\n\n
\n\n\n\n \n \n \"StatisticalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@PhDThesis{        donato2014-statistical,\n    author       = {Donato, Stephanie M},\n    year         = {2014},\n    title        = {Statistical Analysis and Graphic Representation of the\n                   Correlation of Bach and Chopin Preludes},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    school       = {University of Vermont},\n    type         = {Honors College Thesis},\n    url          = {https://scholarworks.uvm.edu/hcoltheses/25/}\n}\n\n
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\n \n\n \n \n \n \n \n Towards modeling texture in symbolic data.\n \n \n \n\n\n \n Giraud, M.; Levé, F.; Mercier, F.; Rigaudière, M.; and Thorez, D.\n\n\n \n\n\n\n In Proceedings of 15th International Society for Music Information Retrieval Conference, pages 59–64, 2014. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    giraud.ea2014-towards,\n    author       = {Giraud, Mathieu and Lev{\\'{e}}, Florence and Mercier,\n                   Florent and Rigaudi{\\`{e}}re, Marc and Thorez, Donatien},\n    year         = {2014},\n    title        = {Towards modeling texture in symbolic data},\n    booktitle    = {Proceedings of 15th International Society for Music\n                   Information Retrieval Conference},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {59--64}\n}\n\n
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\n \n\n \n \n \n \n \n Listening for Tertiary Rhetoric in Haydn's Op. 77 String Quartets.\n \n \n \n\n\n \n Grave, F. K.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 4(Spring): 1–27. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          grave2014-listening,\n    author       = {Grave, Floyd K.},\n    year         = {2014},\n    title        = {Listening for Tertiary Rhetoric in Haydn's Op. 77 String\n                   Quartets},\n    abstract     = {In a pair of recent essays, Elaine Sisman has advanced a\n                   novel approach to the critical analysis of\n                   eighteenth-century instrumental works whose invention and\n                   publication fall within the familiar custom of the opus\n                   group. Citing George Kennedy's distinction between two\n                   species of rhetoric—primary (the speech act itself) and\n                   secondary (involved with the reflective practice of\n                   rhetorical analysis)—Sisman proposes a third kind, a\n                   tertiary rhetoric by which we may imagine the works in an\n                   opus group to be engaged in conversation among themselves.\n                   Because the rhetorical field envisaged by Sisman's concept\n                   normally comprises a full set of six works (or two\n                   sub-groups of three each), the possibilities of tertiary\n                   rhetoric are naturally limited in an opus that a composer\n                   has left unfinished—limited but not necessarily\n                   vitiated. In a famous case of the unfinished opus, Haydn's\n                   Op. 77, which comprises just two quartets, we can discern\n                   an array of complementary relationships, stylistic\n                   dichotomies, and telling points of intersection by which\n                   the two pieces are variously opposed or bound together.\n                   The strands of an imaginary dialogue are thus in place, a\n                   musical conversation from which fresh insight into the\n                   music and its composer can be gained as we listen to the\n                   quartets' discourse over such topics as tonal orientation,\n                   thematic construction, motivic process, ensemble play,\n                   rhetorical strategy, and the ingredients of structural\n                   cohesion.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {Spring},\n    pages        = {1--27},\n    volume       = {4}\n}\n\n
\n
\n\n\n
\n In a pair of recent essays, Elaine Sisman has advanced a novel approach to the critical analysis of eighteenth-century instrumental works whose invention and publication fall within the familiar custom of the opus group. Citing George Kennedy's distinction between two species of rhetoric—primary (the speech act itself) and secondary (involved with the reflective practice of rhetorical analysis)—Sisman proposes a third kind, a tertiary rhetoric by which we may imagine the works in an opus group to be engaged in conversation among themselves. Because the rhetorical field envisaged by Sisman's concept normally comprises a full set of six works (or two sub-groups of three each), the possibilities of tertiary rhetoric are naturally limited in an opus that a composer has left unfinished—limited but not necessarily vitiated. In a famous case of the unfinished opus, Haydn's Op. 77, which comprises just two quartets, we can discern an array of complementary relationships, stylistic dichotomies, and telling points of intersection by which the two pieces are variously opposed or bound together. The strands of an imaginary dialogue are thus in place, a musical conversation from which fresh insight into the music and its composer can be gained as we listen to the quartets' discourse over such topics as tonal orientation, thematic construction, motivic process, ensemble play, rhetorical strategy, and the ingredients of structural cohesion.\n
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\n \n\n \n \n \n \n \n Statistics in Historical Musicology.\n \n \n \n\n\n \n Gustar, A.\n\n\n \n\n\n\n Ph.D. Thesis, Open University, 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        gustar2014-statistics,\n    author       = {Gustar, Andrew},\n    year         = {2014},\n    title        = {Statistics in Historical Musicology},\n    keywords     = {music and mathematics},\n    mendeley-tags= {music and mathematics},\n    school       = {Open University},\n    type         = {Ph.D. Dissertation}\n}\n\n
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\n \n\n \n \n \n \n \n Unisons in Haydn's String Quartets by Mary Hunter.\n \n \n \n\n\n \n Hunter, M.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 4(Spring). 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          hunter2014-unisons,\n    author       = {Hunter, Mary},\n    year         = {2014},\n    title        = {Unisons in Haydn's String Quartets by Mary Hunter},\n    abstract     = {In this essay, I build on Janet Levy's work on the\n                   signification of unisons, and that of Armin Raab on their\n                   structural functions in Haydn's quartets to examine how\n                   unisons convey meanings in these works. I argue that one\n                   of the most salient characteristics of the unison in the\n                   quartets is its capacity for both syntactic and semantic\n                   ambiguity. I also briefly discuss the peculiar status on\n                   the unison in a genre especially valued for its complex\n                   “conversational” textures. I.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {Spring},\n    volume       = {4}\n}\n\n
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\n In this essay, I build on Janet Levy's work on the signification of unisons, and that of Armin Raab on their structural functions in Haydn's quartets to examine how unisons convey meanings in these works. I argue that one of the most salient characteristics of the unison in the quartets is its capacity for both syntactic and semantic ambiguity. I also briefly discuss the peculiar status on the unison in a genre especially valued for its complex “conversational” textures. I.\n
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\n \n\n \n \n \n \n \n \n Sonata form Experimentation in Joseph Haydn's String Quartets, Opus 17.\n \n \n \n \n\n\n \n MacKay, J. S.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 4(1): 1–31. 2014.\n \n\n\n\n
\n\n\n\n \n \n \"SonataPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          mackay2014-sonata,\n    author       = {MacKay, James S.},\n    year         = {2014},\n    title        = {Sonata form Experimentation in Joseph Haydn's String\n                   Quartets, Opus 17},\n    abstract     = {In 1963, Jens Peter Larsen published an article entitled\n                   “Sonata Form Problems,” in which he outlines some of\n                   Haydn's unique solutions to sonata-exposition structures.\n                   Using Larsen's hypotheses, coupled with William Caplin's\n                   insights in Classical Form, and James Hepokoski and Warren\n                   Darcy's ground-breaking Elements of Sonata Theory, I will\n                   examine the diversity of Haydn's formal procedures in\n                   certain movements of his oft-neglected Opus 17 string\n                   quartets of 1771. These works provide a staggering array\n                   of sonata-form possibilities, many of which deviate\n                   provocatively from the High Classical sonata form model.\n                   In a brief overview of the Opus 17 quartets' 17\n                   sonata-form movements (presented in tabular form), we will\n                   explore the diversity of Haydn's formal procedures. Four\n                   of James Hepokoski and Warren Darcy's five sonata-form\n                   “types” (from their Elements of Sonata Theory) are\n                   employed in Opus 17: Type 1 sonatas (which lack a\n                   development section), Type 2 sonatas (which omit the main\n                   theme from the recapitulation), Type 3 sonatas (the\n                   “textbook” form), and Type 4 sonatas (a sonata-rondo\n                   blend). Following this overview, we will turn in depth to\n                   three specific movements from this opus: the slow\n                   movements of Opus 17, nos. 1 and 3, and the sonata-rondo\n                   finale of Opus 17, no. 1. In these works, Haydn's fondness\n                   for anomalous thematic structures will be explored and\n                   examined as viable alternatives to normative sonata-form\n                   design. Haydn's formal inventiveness in his Opus 17\n                   quartets strongly suggests that he was not seeking to\n                   problematize sonata form, but rather, positing a wide\n                   range of solutions for the balance of thematic and\n                   developmental activity in these works.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {1--31},\n    url          = {https://www.rit.edu/affiliate/haydn/sonata-form-experimentation-joseph-haydn's-string-quartets-opus-17},\n    volume       = {4}\n}\n\n
\n
\n\n\n
\n In 1963, Jens Peter Larsen published an article entitled “Sonata Form Problems,” in which he outlines some of Haydn's unique solutions to sonata-exposition structures. Using Larsen's hypotheses, coupled with William Caplin's insights in Classical Form, and James Hepokoski and Warren Darcy's ground-breaking Elements of Sonata Theory, I will examine the diversity of Haydn's formal procedures in certain movements of his oft-neglected Opus 17 string quartets of 1771. These works provide a staggering array of sonata-form possibilities, many of which deviate provocatively from the High Classical sonata form model. In a brief overview of the Opus 17 quartets' 17 sonata-form movements (presented in tabular form), we will explore the diversity of Haydn's formal procedures. Four of James Hepokoski and Warren Darcy's five sonata-form “types” (from their Elements of Sonata Theory) are employed in Opus 17: Type 1 sonatas (which lack a development section), Type 2 sonatas (which omit the main theme from the recapitulation), Type 3 sonatas (the “textbook” form), and Type 4 sonatas (a sonata-rondo blend). Following this overview, we will turn in depth to three specific movements from this opus: the slow movements of Opus 17, nos. 1 and 3, and the sonata-rondo finale of Opus 17, no. 1. In these works, Haydn's fondness for anomalous thematic structures will be explored and examined as viable alternatives to normative sonata-form design. Haydn's formal inventiveness in his Opus 17 quartets strongly suggests that he was not seeking to problematize sonata form, but rather, positing a wide range of solutions for the balance of thematic and developmental activity in these works.\n
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\n \n\n \n \n \n \n \n \n Symbolic Segmentation: A Corpus-Based Analysis of Melodic Phrases.\n \n \n \n \n\n\n \n Rodríguez-López, M.; and Volk, A.\n\n\n \n\n\n\n In Aramaki, M.; Derrien, O.; Kronland-Martinet, R.; and Ystad, S., editor(s), Proc. 10th International Symposium on Computer Music Multidisciplinary Research (CMMR), pages 548–557, Cham, 2014. Springer International Publishing\n \n\n\n\n
\n\n\n\n \n \n \"SymbolicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    rodriguez-lopez.ea2014-symbolic,\n    author       = {Rodr{\\'{i}}guez-L{\\'{o}}pez, Marcelo and Volk, Anja},\n    year         = {2014},\n    title        = {Symbolic Segmentation: A Corpus-Based Analysis of Melodic\n                   Phrases},\n    abstract     = {Gestalt-based segmentation models constitute the current\n                   state of the art in automatic segmentation of melodies.\n                   These models commonly assume that segment boundary\n                   perception is mainly triggered by local discontinuities,\n                   i.e. by abrupt changes in pitch and/or duration between\n                   neighbouring notes. This paper presents a statistical\n                   study of a large corpus of boundary-annotated vocal\n                   melodies to test this assumption. The study focuses on\n                   analysing the statistical behaviour of pitch and duration\n                   in the neighbourhood of annotated phrase boundaries. Our\n                   analysis shows duration discontinuities to be\n                   statistically regular and homogeneous, and contrarily\n                   pitch discontinuities to be irregular and heterogeneous.\n                   We conclude that pitch discontinuities, when modelled as a\n                   local and idiom-independent phenomenon, can only serve as\n                   a weak predictor of segment boundary perception in vocal\n                   melodies.},\n    address      = {Cham},\n    booktitle    = {Proc. 10th International Symposium on Computer Music\n                   Multidisciplinary Research (CMMR)},\n    editor       = {Aramaki, Mitsuko and Derrien, Olivier and\n                   Kronland-Martinet, Richard and Ystad, S{\\o}lvi},\n    isbn         = {978-3-319-12976-1},\n    keywords     = {Interval Size,Music Information Retrieval,Phrase\n                   Boundary,Pitch Interval,Segmentation Model,music\n                   information retrieval},\n    mendeley-tags= {music information retrieval},\n    pages        = {548--557},\n    publisher    = {Springer International Publishing},\n    url          = {https://link.springer.com/chapter/10.1007/978-3-319-12976-1_33}\n}\n\n
\n
\n\n\n
\n Gestalt-based segmentation models constitute the current state of the art in automatic segmentation of melodies. These models commonly assume that segment boundary perception is mainly triggered by local discontinuities, i.e. by abrupt changes in pitch and/or duration between neighbouring notes. This paper presents a statistical study of a large corpus of boundary-annotated vocal melodies to test this assumption. The study focuses on analysing the statistical behaviour of pitch and duration in the neighbourhood of annotated phrase boundaries. Our analysis shows duration discontinuities to be statistically regular and homogeneous, and contrarily pitch discontinuities to be irregular and heterogeneous. We conclude that pitch discontinuities, when modelled as a local and idiom-independent phenomenon, can only serve as a weak predictor of segment boundary perception in vocal melodies.\n
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\n \n\n \n \n \n \n \n What Beethoven learned from K464.\n \n \n \n\n\n \n Rumph, S.\n\n\n \n\n\n\n Eighteenth Century Music, 11(1): 55–77. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          rumph2014-what,\n    author       = {Rumph, Stephen},\n    year         = {2014},\n    title        = {What Beethoven learned from K464},\n    doi          = {10.1017/S1478570613000377},\n    journal      = {Eighteenth Century Music},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1},\n    pages        = {55--77},\n    publisher    = {Cambridge University Press},\n    volume       = {11}\n}\n\n
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\n \n\n \n \n \n \n \n \n Creating research corpora for the computational study of music: The case of the CompMusic project.\n \n \n \n \n\n\n \n Serra, X.\n\n\n \n\n\n\n In Proceedings of the AES International Conference, pages 1–9, London, UK, 2014. \n \n\n\n\n
\n\n\n\n \n \n \"CreatingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    serra2014-creating,\n    author       = {Serra, Xavier},\n    year         = {2014},\n    title        = {Creating research corpora for the computational study of\n                   music: The case of the CompMusic project},\n    abstract     = {A fundamental concern in music information research is\n                   the use of appropriate data sets, research corpora, from\n                   which to perform the needed data processing tasks. These\n                   corpora have to be suited for the specific research\n                   problems to be addressed and the design criteria with\n                   which to create them is a research task to which not much\n                   attention has been paid. In the CompMusic project we are\n                   studying several non-western art music traditions and a\n                   major effort has been the creation of appropriate data\n                   collections with which to study and characterise the\n                   melodic and rhythmic aspects of these traditions. In this\n                   article we go over the criteria used to create these\n                   collections and we describe the specificities of each of\n                   the collections gathered.},\n    address      = {London, UK},\n    booktitle    = {Proceedings of the AES International Conference},\n    isbn         = {9781632662842},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {1--9},\n    url          = {https://repositori.upf.edu/bitstream/handle/10230/44221/serra_aes53_crea.pdf?sequence=1&isAllowed=y}\n}\n\n
\n
\n\n\n
\n A fundamental concern in music information research is the use of appropriate data sets, research corpora, from which to perform the needed data processing tasks. These corpora have to be suited for the specific research problems to be addressed and the design criteria with which to create them is a research task to which not much attention has been paid. In the CompMusic project we are studying several non-western art music traditions and a major effort has been the creation of appropriate data collections with which to study and characterise the melodic and rhythmic aspects of these traditions. In this article we go over the criteria used to create these collections and we describe the specificities of each of the collections gathered.\n
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\n \n\n \n \n \n \n \n \n Quantifying and Visualizing Tonal Complexity.\n \n \n \n \n\n\n \n Weiß, C.; and Müller, M.\n\n\n \n\n\n\n In Proceedings ofthe 9th Conference on Interdisciplinary Musicology, Berlin, 2014. \n \n\n\n\n
\n\n\n\n \n \n \"QuantifyingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    wei.ea2014-quantifying,\n    author       = {Wei{\\ss}, Christof and M{\\"{u}}ller, Meinard},\n    year         = {2014},\n    title        = {Quantifying and Visualizing Tonal Complexity},\n    abstract     = {In Western classical music, the structure of a piece is\n                   reinforced by the contrasting harmonic nature of its\n                   sections. The structural parts are characterized by the\n                   presence of certain chords or chord changes. A section\n                   that is harmonically stable may be followed by a\n                   contrasting section that feels unstable or tense. In the\n                   sonata form, for example, the unstable development part is\n                   located between the stable exposition and recapitulation\n                   phases. In this paper, we try to measure this kind of\n                   harmonic stability and present visualizations for such\n                   analyses. To this end, we propose novel features for\n                   quantifying tonal complexity and discuss their\n                   musicological implications. The features are based on\n                   statistical measures calculated from chroma\n                   representations of the music recording. The\n                   characteristics of tonal complexity apply to different\n                   time scales. To illustrate this time scale dependence for\n                   the proposed features, we use hierarchical visualizations\n                   based on previously introduced scape plot representations.\n                   On a fine temporal level, tonal complexity is related the\n                   character of chords or scales. For example, in a\n                   modulating transition phase, we usually find more complex\n                   chords than at the beginning of a piece. To analyze such\n                   differences, we study the feature values for isolated\n                   chords. Looking at a coarser level, the presence of\n                   modulations is an indication for a segment's complexity.\n                   In the sonata form, for example, the development usually\n                   contains several modulations. To account for this\n                   property, we calculate the complexity features based on a\n                   coarse resolution of the chroma features. For evaluation\n                   of this coarse-scale complexity, we analyze Beethoven's\n                   sonatas where we find higher complexity in the development\n                   parts.},\n    address      = {Berlin},\n    booktitle    = {Proceedings ofthe 9th Conference on Interdisciplinary\n                   Musicology},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {January 2014},\n    url          = {https://www.researchgate.net/publication/303667504_Quantifying_and_Visualizing_Tonal_Complexity}\n}\n\n
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\n In Western classical music, the structure of a piece is reinforced by the contrasting harmonic nature of its sections. The structural parts are characterized by the presence of certain chords or chord changes. A section that is harmonically stable may be followed by a contrasting section that feels unstable or tense. In the sonata form, for example, the unstable development part is located between the stable exposition and recapitulation phases. In this paper, we try to measure this kind of harmonic stability and present visualizations for such analyses. To this end, we propose novel features for quantifying tonal complexity and discuss their musicological implications. The features are based on statistical measures calculated from chroma representations of the music recording. The characteristics of tonal complexity apply to different time scales. To illustrate this time scale dependence for the proposed features, we use hierarchical visualizations based on previously introduced scape plot representations. On a fine temporal level, tonal complexity is related the character of chords or scales. For example, in a modulating transition phase, we usually find more complex chords than at the beginning of a piece. To analyze such differences, we study the feature values for isolated chords. Looking at a coarser level, the presence of modulations is an indication for a segment's complexity. In the sonata form, for example, the development usually contains several modulations. To account for this property, we calculate the complexity features based on a coarse resolution of the chroma features. For evaluation of this coarse-scale complexity, we analyze Beethoven's sonatas where we find higher complexity in the development parts.\n
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\n  \n 2013\n \n \n (12)\n \n \n
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\n \n\n \n \n \n \n \n Melodic contour representations in the analysis of children's songs.\n \n \n \n\n\n \n Anagnostopoulou, C.; Giraud, M.; and Poulakis, N.\n\n\n \n\n\n\n In van Kranenburg, P.; Anagnostopoulou, C.; and Volk, A., editor(s), Proceedings of the Third International Workshop on Folk Music Analysis, pages 40–43, Utrecht, Netherlands, 2013. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    anagnostopoulou.ea2013-melodic,\n    author       = {Anagnostopoulou, Christina and Giraud, Mathieu and\n                   Poulakis, Nick},\n    year         = {2013},\n    title        = {Melodic contour representations in the analysis of\n                   children's songs},\n    address      = {Utrecht, Netherlands},\n    booktitle    = {Proceedings of the Third International Workshop on Folk\n                   Music Analysis},\n    editor       = {van Kranenburg, Peter and Anagnostopoulou, Christina and\n                   Volk, Anja},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {40--43}\n}\n\n
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\n \n\n \n \n \n \n \n \n Partitional Analysis and Rhythmic Partitioning: Mediations Between Rhythm and Texture.\n \n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n In 13th International Music Theory Conference, pages 44–51, Vilnius, Lituania, 2013. \n \n\n\n\n
\n\n\n\n \n \n \"PartitionalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    gentil-nunes2013-partitional,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2013},\n    title        = {Partitional Analysis and Rhythmic Partitioning:\n                   Mediations Between Rhythm and Texture},\n    address      = {Vilnius, Lituania},\n    booktitle    = {13th International Music Theory Conference},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    pages        = {44--51},\n    url          = {http://pmc.lmta.lt/EN.html}\n}\n\n
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\n \n\n \n \n \n \n \n \n On the Virtuous and the Vexatious in an Age of Big Data.\n \n \n \n \n\n\n \n Huron, D.\n\n\n \n\n\n\n Music Perception, 31(1): 4–9. sep 2013.\n \n\n\n\n
\n\n\n\n \n \n \"OnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          huron2013-virtuous,\n    author       = {Huron, David},\n    year         = {2013},\n    title        = {On the Virtuous and the Vexatious in an Age of Big Data},\n    doi          = {10.1525/mp.2013.31.1.4},\n    issn         = {0730-7829},\n    journal      = {Music Perception},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    month        = {sep},\n    number       = {1},\n    pages        = {4--9},\n    url          = {https://online.ucpress.edu/mp/article/31/1/4/62591/On-the-Virtuous-and-the-Vexatious-in-an-Age-of-Big},\n    volume       = {31}\n}\n\n
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\n \n\n \n \n \n \n \n \n Expecting the Unexpected: Haydn's Three-Part Expositions.\n \n \n \n \n\n\n \n Ludwig, A. R.\n\n\n \n\n\n\n Lumen: Selected Proceedings from the Canadian Society for Eighteenth-Century Studies, 32: 31. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"ExpectingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          ludwig2013-expecting,\n    author       = {Ludwig, Alexander Raymond},\n    year         = {2013},\n    title        = {Expecting the Unexpected: Haydn's Three-Part\n                   Expositions},\n    doi          = {10.7202/1015482ar},\n    issn         = {1209-3696},\n    journal      = {Lumen: Selected Proceedings from the Canadian Society for\n                   Eighteenth-Century Studies},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    pages        = {31},\n    url          = {https://www.erudit.org/en/journals/lumen/2013-v32-lumen0563/1015482ar/\n                   http://id.erudit.org/iderudit/1015482ar},\n    volume       = {32}\n}\n\n
\n
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\n \n\n \n \n \n \n \n Franz Joseph Haydn and the Five-Octave Classical Keyboard: Registral Extremes, Formal Emphases and Tonal Strategies.\n \n \n \n\n\n \n MacKay, J. S.\n\n\n \n\n\n\n Canadian University Music Review, 23(1-2): 126–144. 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          mackay2013-franz,\n    author       = {MacKay, James S.},\n    year         = {2013},\n    title        = {Franz Joseph Haydn and the Five-Octave Classical\n                   Keyboard: Registral Extremes, Formal Emphases and Tonal\n                   Strategies},\n    abstract     = {The Classical keyboard in its various forms (harpsichord,\n                   clavichord and fortepiano) typically had a modest\n                   five-octave range (FF–f 3 ) prior to ca. 1800. This\n                   essay examines how this range influenced the tonal shape\n                   of Joseph Haydn's keyboard music written after 1765. The\n                   author explores how Haydn used registral extremes to\n                   emphasize major formal junctures, cadences and\n                   modulations. Finally, he explores how the presence or\n                   absence of the keyboard's extreme pitches contributes to\n                   key character, examining the different contexts in which\n                   Haydn uses them in three tonalities: D minor, C major and\n                   A major. Avant environ 1800, les diff{\\'{e}}rentes formes\n                   d'instruments {\\`{a}} clavier classiques (clavecin,\n                   clavicorde et pianoforte) comportaient un modeste ambitus\n                   de cinq octaves (de deux octaves et demie sous le do\n                   central {\\`{a}} fa deux octaves et demie au-dessus du do\n                   central). Le pr{\\'{e}}sent essai analyse comment cet\n                   ambitus influe sur le contour tonal de la musique pour\n                   clavier de Joseph Haydn, {\\'{e}}crite apr{\\`{e}}s 1765.\n                   L'auteur d{\\'{e}}montre comment Haydn utilisait les\n                   extr{\\'{e}}mit{\\'{e}}s du registre pour mettre en relief\n                   les principaux points de jonction formels, les cadences et\n                   les modulations importantes. Enfin, il signale comment la\n                   pr{\\'{e}}sence ou l'absence des hauteurs extr{\\^{e}}mement\n                   graves ou aigu{\\"{e}}s du clavier contribue {\\`{a}}\n                   accentuer le caract{\\`{e}}re de la tonalit{\\'{e}}. Pour ce\n                   faire, il {\\'{e}}tudie diff{\\'{e}}rents contextes dans\n                   lesquels Haydn les emploie : r{\\'{e}} mineur, do majeur et la majeur.},\n    doi          = {10.7202/1014521ar},\n    issn         = {0710-0353},\n    journal      = {Canadian University Music Review},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1-2},\n    pages        = {126--144},\n    volume       = {23}\n}\n\n
\n
\n\n\n
\n The Classical keyboard in its various forms (harpsichord, clavichord and fortepiano) typically had a modest five-octave range (FF–f 3 ) prior to ca. 1800. This essay examines how this range influenced the tonal shape of Joseph Haydn's keyboard music written after 1765. The author explores how Haydn used registral extremes to emphasize major formal junctures, cadences and modulations. Finally, he explores how the presence or absence of the keyboard's extreme pitches contributes to key character, examining the different contexts in which Haydn uses them in three tonalities: D minor, C major and A major. Avant environ 1800, les différentes formes d'instruments à clavier classiques (clavecin, clavicorde et pianoforte) comportaient un modeste ambitus de cinq octaves (de deux octaves et demie sous le do central à fa deux octaves et demie au-dessus du do central). Le présent essai analyse comment cet ambitus influe sur le contour tonal de la musique pour clavier de Joseph Haydn, écrite après 1765. L'auteur démontre comment Haydn utilisait les extrémités du registre pour mettre en relief les principaux points de jonction formels, les cadences et les modulations importantes. Enfin, il signale comment la présence ou l'absence des hauteurs extrêmement graves ou aiguës du clavier contribue à accentuer le caractère de la tonalité. Pour ce faire, il étudie différents contextes dans lesquels Haydn les emploie : ré mineur, do majeur et la majeur.\n
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\n \n\n \n \n \n \n \n \n The Implementation of a Contour Module for Music21.\n \n \n \n \n\n\n \n Sampaio, M.; Kroger, P.; Menezes, M. P.; da Rocha, J. M.; Ourives, N. d. S.; and de Carvalho, D. Q.\n\n\n \n\n\n\n ART Music Review, 24. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          sampaio.ea2013-implementation,\n    author       = {{Sampaio}, {Marcos da Silva} and Kroger, Pedro and\n                   Menezes, Mara Pinheiro and da Rocha, Jean Menezes and\n                   Ourives, Natanael de Souza and de Carvalho, Dennis\n                   Queiroz},\n    year         = {2013},\n    title        = {The Implementation of a Contour Module for Music21},\n    journal      = {ART Music Review},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    url          = {http://www.revista-art.com/the-implementation-of-a-contour-module-for-music21},\n    volume       = {24}\n}\n\n
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\n \n\n \n \n \n \n \n \n Toward a new comparative musicology.\n \n \n \n \n\n\n \n Savage, P.; and Brown, S.\n\n\n \n\n\n\n Analytical Approaches to World Music, 2(2): 148–197. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"TowardPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          savage.ea2013-toward,\n    author       = {Savage, Patrick and Brown, Steven},\n    year         = {2013},\n    title        = {Toward a new comparative musicology},\n    abstract     = {We propose a return to the forgotten agenda of\n                   comparative musicology, one that is updated with the\n                   paradigms of modern evolutionary theory and scientific\n                   methodology. Ever since the field of comparative\n                   musicology became redefined as ethnomusicology in the\n                   mid-20th century, its original research agenda has been\n                   all but abandoned by musicologists, not least the\n                   overarching goal of cross-cultural musical comparison. We\n                   outline here five major themes that underlie the\n                   re-establishment of comparative musicology: (1)\n                   classification, (2) cultural evolution, (3) human history,\n                   (4) universals, and (5) biological evolution. Throughout\n                   the article, we clarify key ideological, methodological\n                   and terminological objections that have been levied\n                   against musical comparison. Ultimately, we argue for an\n                   inclusive, constructive, and multidisciplinary field that\n                   analyzes the world's musical diversity, from the broadest\n                   of generalities to the most culture-specific particulars,\n                   with the aim of synthesizing the full range of theoretical\n                   perspectives and research methodologies available.},\n    doi          = {10.31234/osf.io/q3egp},\n    journal      = {Analytical Approaches to World Music},\n    keywords     = {Biomusicology,Constructive,Ethnomusicology,Humanities,Ideology,Musicology,Problem\n                   of universals,Psychology,Scientific method,Social\n                   science,Sociocultural evolution,computational musicology},\n    mendeley-tags= {computational musicology},\n    number       = {2},\n    pages        = {148--197},\n    url          = {https://www.researchgate.net/publication/283088191_Toward_a_new_comparative_musicology},\n    volume       = {2}\n}\n\n
\n
\n\n\n
\n We propose a return to the forgotten agenda of comparative musicology, one that is updated with the paradigms of modern evolutionary theory and scientific methodology. Ever since the field of comparative musicology became redefined as ethnomusicology in the mid-20th century, its original research agenda has been all but abandoned by musicologists, not least the overarching goal of cross-cultural musical comparison. We outline here five major themes that underlie the re-establishment of comparative musicology: (1) classification, (2) cultural evolution, (3) human history, (4) universals, and (5) biological evolution. Throughout the article, we clarify key ideological, methodological and terminological objections that have been levied against musical comparison. Ultimately, we argue for an inclusive, constructive, and multidisciplinary field that analyzes the world's musical diversity, from the broadest of generalities to the most culture-specific particulars, with the aim of synthesizing the full range of theoretical perspectives and research methodologies available.\n
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\n \n\n \n \n \n \n \n Using multivariate statistics.\n \n \n \n\n\n \n Tabachnick, B. G.; and Fidell, L. S.\n\n\n \n\n\n\n of Always learningPearson, Boston Munich, 6. ed., international ed edition, 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Book{             tabachnick.ea2013-using,\n    author       = {Tabachnick, Barbara G. and Fidell, Linda S.},\n    year         = {2013},\n    title        = {Using multivariate statistics},\n    address      = {Boston Munich},\n    edition      = {6. ed., international ed},\n    series       = {Always learning},\n    isbn         = {978-0-205-89081-1 978-1-292-02131-7},\n    language     = {eng},\n    publisher    = {Pearson},\n    annote       = {Previous ed.: Boston, Mass.; London: Allyn and Bacon,\n                   2006. - Includes bibliographical references and index}\n}\n\n
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\n \n\n \n \n \n \n \n \n Statistical Analysis of Harmony and Melody in Rock Music.\n \n \n \n \n\n\n \n Temperley, D.; and de Clercq, T.\n\n\n \n\n\n\n Journal of New Music Research, 42(3): 187–204. 2013.\n \n\n\n\n
\n\n\n\n \n \n \"StatisticalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          temperley.ea2013-statistical,\n    author       = {Temperley, David and de Clercq, Trevor},\n    year         = {2013},\n    title        = {Statistical Analysis of Harmony and Melody in Rock\n                   Music},\n    abstract     = {We present a corpus of harmonic analyses and melodic\n                   tran- scriptions of rock songs. After explaining the\n                   creation and notation of the corpus, we present results of\n                   some explorations of the corpus data. We begin by\n                   considering the overall dis- tribution of scale-degrees in\n                   rock. We then address the issue of key-finding: how the\n                   key of a rock song can be identified from harmonic and\n                   melodic information. Considering both the distribution of\n                   melodic scale-degrees and the distribution of chords\n                   (roots), as well as the metrical placement of chords,\n                   leads to good key-finding performance. Finally, we discuss\n                   how songs within the corpus might be categorized with\n                   regard to their pitch organization. Statistical\n                   categorization methods point to a clustering of songs that\n                   resembles the major/minor distinction in common-practice\n                   music, though with some im- portant differences. 1.},\n    doi          = {10.1080/09298215.2013.839525},\n    issn         = {17445027},\n    journal      = {Journal of New Music Research},\n    keywords     = {statistics},\n    mendeley-tags= {statistics},\n    number       = {3},\n    pages        = {187--204},\n    url          = {http://davidtemperley.com/wp-content/uploads/2015/11/temperley-declercq-jnmr.pdf},\n    volume       = {42}\n}\n\n
\n
\n\n\n
\n We present a corpus of harmonic analyses and melodic tran- scriptions of rock songs. After explaining the creation and notation of the corpus, we present results of some explorations of the corpus data. We begin by considering the overall dis- tribution of scale-degrees in rock. We then address the issue of key-finding: how the key of a rock song can be identified from harmonic and melodic information. Considering both the distribution of melodic scale-degrees and the distribution of chords (roots), as well as the metrical placement of chords, leads to good key-finding performance. Finally, we discuss how songs within the corpus might be categorized with regard to their pitch organization. Statistical categorization methods point to a clustering of songs that resembles the major/minor distinction in common-practice music, though with some im- portant differences. 1.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Elementary Statistics.\n \n \n \n\n\n \n Triola, M. F.\n\n\n \n\n\n\n Pearson Addison Wesley, Boston, 10 edition, 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             triola2013-elementary,\n    author       = {Triola, Mario F.},\n    year         = {2013},\n    title        = {Elementary Statistics},\n    address      = {Boston},\n    doi          = {10.1136/bmj.1.5135.1458},\n    edition      = {10},\n    isbn         = {9780808924395},\n    issn         = {0959-8138},\n    keywords     = {statistics},\n    mendeley-tags= {statistics},\n    publisher    = {Pearson Addison Wesley}\n}\n\n
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\n \n\n \n \n \n \n \n \n Some Statistical Properties of Tonality, 1650-1900.\n \n \n \n \n\n\n \n White, C. W.\n\n\n \n\n\n\n Ph.D. Thesis, Yale University, 2013.\n \n\n\n\n
\n\n\n\n \n \n \"SomePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@PhDThesis{        white2013-some,\n    author       = {White, Christopher William},\n    year         = {2013},\n    title        = {Some Statistical Properties of Tonality, 1650-1900},\n    abstract     = {This dissertation investigates the statistical properties\n                   present within corpora of common practice music, involving\n                   a data set of more than 8,000 works spanning from 1650 to\n                   1900, and focusing specifically on the properties of the\n                   chord progressions contained therein. In the first\n                   chapter, methodologies concerning corpus analysis are\n                   presented and contrasted with text-based methodologies. It\n                   is argued that corpus analyses not only can show\n                   large-scale trends within data, but can empirically test\n                   and formalize traditional or inherited music theories,\n                   while also modeling corpora as a collection of discursive\n                   and communicative materials. Concerning the idea of corpus\n                   analysis as an analysis of discourse, literature\n                   concerning musical communication and learning is reviewed,\n                   and connections between corpus analysis and statistical\n                   learning are explored. After making this connection, we\n                   explore several problems with models of musical\n                   communication (e.g., music's composers and listeners\n                   likely use different cognitive models for their respective\n                   production and interpretation) and several implications of\n                   connecting corpora to cognitive models (e.g., a model's\n                   dependency on a particular historical situation). Chapter\n                   2 provides an overview of literature concerning\n                   computational musical analysis. The divide between\n                   top-down systems and bottom-up systems is discussed, and\n                   examples of each are reviewed. The chapter ends with an\n                   examination of more recent applications of information\n                   theory in music analysis. Chapter 3 considers various ways\n                   corpora can be grouped as well as the implications those\n                   grouping techniques have on notions of musical style. It\n                   is hypothesized that the evolution of musical style can be\n                   modeled through the interaction of corpus statistics,\n                   chronological eras, and geographic contexts. This idea is\n                   tested by quantifying the probabilities of various\n                   composers' chord progressions, and cluster analyses are\n                   performed on these data. Various ways to divide and group\n                   corpora are considered, modeled, and tested. In the fourth\n                   chapter, this dissertation investigates notions of\n                   harmonic vocabulary and syntax, hypothesizing that music\n                   involves syntactic regularity in much the same way as\n                   occurs in spoken languages. This investigation first\n                   probes this hypothesis through a corpus analysis of the\n                   Bach chorales, identifying potential syntactic/functional\n                   categories using a Hidden Markov Model. The analysis\n                   produces a three-function model as well as models with\n                   higher numbers of functions. In the end, the data suggest\n                   that music does indeed involve regularities, while also\n                   arguing for a definition of chord function that adds\n                   subtlety to models used by traditional music theory. A\n                   number of implications are considered, including the\n                   interaction of chord frequency and chord function, and the\n                   preeminence of triads in the resulting syntactic models.\n                   Chapter 5 considers a particularly difficult problem of\n                   corpus analysis as it relates to musical vocabulary and\n                   syntax: the variegated and complex musical surface. One\n                   potential algorithm for vocabulary reduction is presented.\n                   This algorithm attempts to change each chord within an\n                   n-grams to its subset or superset that maximizes the\n                   probability of that trigram occurring. When a corpus of\n                   common-practice music is processed using this algorithm, a\n                   standard tertian chord vocabulary results, along with a\n                   bigram chord syntax that adheres to our intuitions\n                   concerning standard chord function. In the sixth chapter,\n                   this study probes the notion of musical key as it concerns\n                   communication, suggesting that if musical practice is\n                   constrained by its point in history and progressions of\n                   chords exhibit syntactic regularities, then one should be\n                   able to build a key-finding model that learns to identify\n                   key by observing some historically situated corpus. Such a\n                   model is presented, and is trained on the music of a\n                   variety of different historical periods. The model then\n                   analyzes two famous moments of musical ambiguity: the\n                   openings of Beethoven's Eroica and Wagner's prelude to\n                   Tristan und Isolde. The results confirm that different\n                   corpus-trained models produce subtly different behavior.\n                   The dissertation ends by considering several general and\n                   summarizing issues, for instance the notion that there are\n                   many historically-situated tonal models within Western\n                   music history, and that the difference between listening\n                   and compositional models likely accounts for the gap\n                   between the complex statistics of the tonal tradition and\n                   traditional concepts in music theory.},\n    isbn         = {9781303715631},\n    keywords     = {0290:Linguistics,0413:Music,Communication and the\n                   arts,Computation,Data\n                   mining,Language,Linguistics,Modeling,Music,Music\n                   theory,Musicology,literature and linguistics,music and\n                   mathematics},\n    mendeley-tags= {music and mathematics},\n    number       = {December},\n    pages        = {332},\n    pmid         = {1495950055},\n    school       = {Yale University},\n    type         = {Ph.D. Dissertation},\n    url          = {https://search.proquest.com/docview/1495950055?accountid=26641%5Cnhttp://link.periodicos.capes.gov.br/sfxlcl41?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&genre=dissertations+%26+theses&sid=ProQ:ProQuest+Dissertations+%26+Theses+Glob}\n}\n\n
\n
\n\n\n
\n This dissertation investigates the statistical properties present within corpora of common practice music, involving a data set of more than 8,000 works spanning from 1650 to 1900, and focusing specifically on the properties of the chord progressions contained therein. In the first chapter, methodologies concerning corpus analysis are presented and contrasted with text-based methodologies. It is argued that corpus analyses not only can show large-scale trends within data, but can empirically test and formalize traditional or inherited music theories, while also modeling corpora as a collection of discursive and communicative materials. Concerning the idea of corpus analysis as an analysis of discourse, literature concerning musical communication and learning is reviewed, and connections between corpus analysis and statistical learning are explored. After making this connection, we explore several problems with models of musical communication (e.g., music's composers and listeners likely use different cognitive models for their respective production and interpretation) and several implications of connecting corpora to cognitive models (e.g., a model's dependency on a particular historical situation). Chapter 2 provides an overview of literature concerning computational musical analysis. The divide between top-down systems and bottom-up systems is discussed, and examples of each are reviewed. The chapter ends with an examination of more recent applications of information theory in music analysis. Chapter 3 considers various ways corpora can be grouped as well as the implications those grouping techniques have on notions of musical style. It is hypothesized that the evolution of musical style can be modeled through the interaction of corpus statistics, chronological eras, and geographic contexts. This idea is tested by quantifying the probabilities of various composers' chord progressions, and cluster analyses are performed on these data. Various ways to divide and group corpora are considered, modeled, and tested. In the fourth chapter, this dissertation investigates notions of harmonic vocabulary and syntax, hypothesizing that music involves syntactic regularity in much the same way as occurs in spoken languages. This investigation first probes this hypothesis through a corpus analysis of the Bach chorales, identifying potential syntactic/functional categories using a Hidden Markov Model. The analysis produces a three-function model as well as models with higher numbers of functions. In the end, the data suggest that music does indeed involve regularities, while also arguing for a definition of chord function that adds subtlety to models used by traditional music theory. A number of implications are considered, including the interaction of chord frequency and chord function, and the preeminence of triads in the resulting syntactic models. Chapter 5 considers a particularly difficult problem of corpus analysis as it relates to musical vocabulary and syntax: the variegated and complex musical surface. One potential algorithm for vocabulary reduction is presented. This algorithm attempts to change each chord within an n-grams to its subset or superset that maximizes the probability of that trigram occurring. When a corpus of common-practice music is processed using this algorithm, a standard tertian chord vocabulary results, along with a bigram chord syntax that adheres to our intuitions concerning standard chord function. In the sixth chapter, this study probes the notion of musical key as it concerns communication, suggesting that if musical practice is constrained by its point in history and progressions of chords exhibit syntactic regularities, then one should be able to build a key-finding model that learns to identify key by observing some historically situated corpus. Such a model is presented, and is trained on the music of a variety of different historical periods. The model then analyzes two famous moments of musical ambiguity: the openings of Beethoven's Eroica and Wagner's prelude to Tristan und Isolde. The results confirm that different corpus-trained models produce subtly different behavior. The dissertation ends by considering several general and summarizing issues, for instance the notion that there are many historically-situated tonal models within Western music history, and that the difference between listening and compositional models likely accounts for the gap between the complex statistics of the tonal tradition and traditional concepts in music theory.\n
\n\n\n
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\n \n\n \n \n \n \n \n \n Digital Musicology and MIR : Papers , Projects and Challenges.\n \n \n \n \n\n\n \n Wiering, F.; and Benetos, E.\n\n\n \n\n\n\n In Brito Jr, A. d. S.; Gouyen, F.; and Dixon, S., editor(s), Proceedings of the 14th International Society for Music Information Retrieval Conference, pages 2–5, Curitiba, 2013. \n \n\n\n\n
\n\n\n\n \n \n \"DigitalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    wiering.ea2013-digital,\n    author       = {Wiering, Frans and Benetos, Emmanouil},\n    year         = {2013},\n    title        = {Digital Musicology and MIR : Papers , Projects and\n                   Challenges},\n    abstract     = {In this paper we report on the ISMIR 2013 Demo and Late\n                   Breaking Session entitled Digital Musicology and MIR. Five\n                   papers were discussed as examples of interest- ing MIR\n                   contributions to musicology. Two important projects,\n                   Transforming Musicology and CompMusic, were briefly\n                   presented. Finally, this paper reports the first results\n                   of a questionnaire about challenges from Digital\n                   Musicology for MIR research. The most important out- comes\n                   are that lack of suitable musical data is still an im-\n                   portant obstacle and that there is a great demand for\n                   tools and methods that make integrated access and analysis\n                   of symbolic and audio data possible.},\n    address      = {Curitiba},\n    booktitle    = {Proceedings of the 14th International Society for Music\n                   Information Retrieval Conference},\n    editor       = {{Brito Jr}, Alceu de Souza and Gouyen, Fabien and Dixon,\n                   Simon},\n    keywords     = {music information retrieval},\n    mendeley-tags= {music information retrieval},\n    pages        = {2--5},\n    url          = {http://www.staff.science.uu.nl/$\\sim$wieri103/publications/WieringBenetosDigitalMusicologyAndMIRfinal.pdf}\n}\n\n
\n
\n\n\n
\n In this paper we report on the ISMIR 2013 Demo and Late Breaking Session entitled Digital Musicology and MIR. Five papers were discussed as examples of interest- ing MIR contributions to musicology. Two important projects, Transforming Musicology and CompMusic, were briefly presented. Finally, this paper reports the first results of a questionnaire about challenges from Digital Musicology for MIR research. The most important out- comes are that lack of suitable musical data is still an im- portant obstacle and that there is a great demand for tools and methods that make integrated access and analysis of symbolic and audio data possible.\n
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\n  \n 2012\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n \n The Loosening Role of Polyphony: Texture and Formal Functions in Mozart's “Haydn” Quartets.\n \n \n \n \n\n\n \n Bakulina, O. E.\n\n\n \n\n\n\n Intersections: Canadian Journal of Music, 32(1-2): 7–42. sep 2012.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          bakulina2012-loosening,\n    author       = {Bakulina, Olga Ellen},\n    year         = {2012},\n    title        = {The Loosening Role of Polyphony: Texture and Formal\n                   Functions in Mozart's “Haydn” Quartets},\n    abstract     = {This essay demonstrates that texture can act as a\n                   form-defining factor by focusing on one specific textural\n                   type: imitative polyphony. Mozart's six quartets dedicated\n                   to Haydn illustrate this claim. Building on William\n                   Caplin's form-functional theory and his distinction\n                   between tight-knit and loose organization, imitative\n                   texture is shown to serve two purposes: as a loosening\n                   device, and as a means of textural and phrase-structural\n                   contrast. To deepen our understanding of polyphony's\n                   formal and expressive roles, two new concepts are\n                   proposed: contrast pair and imitative presentation. The\n                   contrast-pair principle is then explored in select\n                   Viennese quartets by Mozart's contemporaries.},\n    doi          = {10.7202/1018577ar},\n    issn         = {1918-512X},\n    journal      = {Intersections: Canadian Journal of Music},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    month        = {sep},\n    number       = {1-2},\n    pages        = {7--42},\n    url          = {http://id.erudit.org/iderudit/1018577ar},\n    volume       = {32}\n}\n\n
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\n This essay demonstrates that texture can act as a form-defining factor by focusing on one specific textural type: imitative polyphony. Mozart's six quartets dedicated to Haydn illustrate this claim. Building on William Caplin's form-functional theory and his distinction between tight-knit and loose organization, imitative texture is shown to serve two purposes: as a loosening device, and as a means of textural and phrase-structural contrast. To deepen our understanding of polyphony's formal and expressive roles, two new concepts are proposed: contrast pair and imitative presentation. The contrast-pair principle is then explored in select Viennese quartets by Mozart's contemporaries.\n
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\n \n\n \n \n \n \n \n Hepokoski and Darcy's Haydn.\n \n \n \n\n\n \n Ludwig, A.\n\n\n \n\n\n\n Haydn: Online Journal of the Haydn Society of North America, 2(2): 1–27. 2012.\n \n\n\n\n
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@Article{          ludwig2012-hepokoski,\n    author       = {Ludwig, Alexander},\n    year         = {2012},\n    title        = {Hepokoski and Darcy's Haydn},\n    abstract     = {In their massive book Elements of Sonata Theory, James\n                   Hepokoski and Warren Darcy frequently allude to or\n                   explicitly detail Joseph Haydn's well- known proclivity\n                   for using humor and wit. By constantly qualifying Haydn's\n                   music as witty or humorous, they succeed only in\n                   marginalizing both Haydn and his music. But given Haydn's\n                   status and influence as a composer in the late eighteenth\n                   century, this marginalization, historically speaking,\n                   hardly seems accurate. I propose two modifications that\n                   will enhance the overall effectiveness of Hepokoski and\n                   Darcy's theory, particularly as it relates to Haydn's\n                   compositional practices, and thereby soften the theory's\n                   current marginalization of Haydn. First, extracting the\n                   concept of "deformation" entirely and replacing it with a\n                   lower-level default will allow the direct examination of\n                   defaults between composers instead of juxtaposing defaults\n                   and deformations. Second, reconfiguring the foundational\n                   binary opposition from "two-part" or "continuous"\n                   expositions to those "with" or "without" medial caesuras\n                   will effectively open for consideration the previously\n                   excluded "three-part" exposition, a structural type\n                   prominent in Haydn's works. These two changes will help\n                   Hepokoski and Darcy's sonata theory to more fair-mindedly\n                   consider Haydn's music, thereby reshaping their theory\n                   into a more versatile, robust, and historically faithful\n                   tool.},\n    journal      = {Haydn: Online Journal of the Haydn Society of North\n                   America},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {2},\n    pages        = {1--27},\n    volume       = {2}\n}\n\n
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\n\n\n
\n In their massive book Elements of Sonata Theory, James Hepokoski and Warren Darcy frequently allude to or explicitly detail Joseph Haydn's well- known proclivity for using humor and wit. By constantly qualifying Haydn's music as witty or humorous, they succeed only in marginalizing both Haydn and his music. But given Haydn's status and influence as a composer in the late eighteenth century, this marginalization, historically speaking, hardly seems accurate. I propose two modifications that will enhance the overall effectiveness of Hepokoski and Darcy's theory, particularly as it relates to Haydn's compositional practices, and thereby soften the theory's current marginalization of Haydn. First, extracting the concept of \"deformation\" entirely and replacing it with a lower-level default will allow the direct examination of defaults between composers instead of juxtaposing defaults and deformations. Second, reconfiguring the foundational binary opposition from \"two-part\" or \"continuous\" expositions to those \"with\" or \"without\" medial caesuras will effectively open for consideration the previously excluded \"three-part\" exposition, a structural type prominent in Haydn's works. These two changes will help Hepokoski and Darcy's sonata theory to more fair-mindedly consider Haydn's music, thereby reshaping their theory into a more versatile, robust, and historically faithful tool.\n
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\n \n\n \n \n \n \n \n \n A Teoria de Relações de Contornos Musicais: inconsistências, soluções e ferramentas.\n \n \n \n \n\n\n \n Sampaio, M.\n\n\n \n\n\n\n Ph.D. Thesis, Universidade Federal da Bahia, 2012.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@PhDThesis{        sampaio2012-teoria,\n    author       = {{Sampaio}, {Marcos da Silva}},\n    year         = {2012},\n    title        = {A Teoria de Rela{\\c{c}}{\\~{o}}es de Contornos Musicais:\n                   inconsist{\\^{e}}ncias, solu{\\c{c}}{\\~{o}}es e ferramentas},\n    abstract     = {Contorno {\\'{e}} o perfil, desenho ou formato de um\n                   objeto. Em M{\\'{u}}sica, contornos podem ser\n                   abstra{\\'{i}}dos de qualquer par{\\^{a}}metro, como altura,\n                   densidade, ritmo, timbre, e intensidade. O estudo de\n                   rela{\\c{c}}{\\~{o}}es de contornos musicais {\\'{e}}\n                   importante porque tais rela{\\c{c}}{\\~{o}}es s{\\~{a}}o\n                   facilmente reconhec{\\'{i}}veis auditivamente por\n                   m{\\'{u}}sicos e leigos, e porque, assim como conjuntos de\n                   notas e motivos, contornos podem ajudar a dar\n                   coer{\\^{e}}ncia a uma obra musical. A Teoria de\n                   Rela{\\c{c}}{\\~{o}}es de Contornos Musicais foi\n                   desenvolvida por autores como Michael L. Friedmann, Robert\n                   D. Morris, e Elizabeth W. Marvin e Paul Laprade. Esta\n                   teoria fornece conceitos e opera{\\c{c}}{\\~{o}}es que\n                   ajudam a dar precis{\\~{a}}o no estudo das\n                   rela{\\c{c}}{\\~{o}}es de contornos musicais. Eu descobri\n                   que o algoritmo de forma prima de classes de contornos\n                   equivalentes de Marvin e Laprade {\\'{e}} inconsistente.\n                   Baseado na inconsist{\\^{e}}ncia deste algoritmo, levantei\n                   duas hip{\\'{o}}teses: a Teoria dos Contornos cont{\\'{e}}m\n                   inconsist{\\^{e}}ncias em outros pontos al{\\'{e}}m deste\n                   algoritmo; e a inconsist{\\^{e}}ncia deste algoritmo\n                   implica em erros nos desdobramentos e nos resultados das\n                   an{\\'{a}}lises de obras musicais baseadas nesta teoria.\n                   Este trabalho teve duas partes. A primeira teve como\n                   objetivo principal verificar a exist{\\^{e}}ncia de\n                   inconsist{\\^{e}}ncias na Teoria dos Contornos e propor\n                   solu{\\c{c}}{\\~{o}}es. A segunda teve como objetivo compor\n                   um grupo de composi{\\c{c}}{\\~{o}}es com eventual uso de\n                   rela{\\c{c}}{\\~{o}}es de contornos musicais. A metodologia\n                   de verifica{\\c{c}}{\\~{a}}o de inconsist{\\^{e}}ncias\n                   consistiu no desenvolvimento do programa MusiContour e na\n                   realiza{\\c{c}}{\\~{a}}o de testes funcionais. Ent{\\~{a}}o,\n                   programei e testei um conjunto de 37 opera{\\c{c}}{\\~{o}}es\n                   e conceitos da Teoria dos Contornos. Com a pesquisa que\n                   originou este trabalho pude verificar que a primeira\n                   hip{\\'{o}}tese, das inconsist{\\^{e}}ncias em outros pontos\n                   da Teoria dos Contornos, {\\'{e}} verdadeira, e que a\n                   segunda hip{\\'{o}}tese, do impacto da inconsist{\\^{e}}ncia\n                   do algoritmo de Marvin e Laprade, {\\'{e}} falsa. Os\n                   principais resultados deste trabalho s{\\~{a}}o os novos\n                   algoritmos de forma prima de classes de contornos\n                   equivalentes e de redu{\\c{c}}{\\~{a}}o de contornos,\n                   revis{\\~{a}}o de conceitos, opera{\\c{c}}{\\~{o}}es,\n                   defini{\\c{c}}{\\~{a}}o de novas opera{\\c{c}}{\\~{o}}es, o\n                   programa MusiContour, a organiza{\\c{c}}{\\~{a}}o\n                   did{\\'{a}}tica do texto sobre a teoria, e a composi{\\c{c}}{\\~{a}}o e apresenta{\\c{c}}{\\~{a}}o de sete obras musicais.},\n    keywords     = {Composi{\\c{c}}{\\~{a}}o Musical,Contornos\n                   musicais,Programa de computador para M{\\'{u}}sica,Teoria\n                   Musical,Teoria de Rela{\\c{c}}{\\~{o}}es de Contornos\n                   Musicais,music contour},\n    mendeley-tags= {music contour},\n    pages        = {230},\n    school       = {Universidade Federal da Bahia},\n    type         = {Ph.D. Thesis},\n    url          = {https://repositorio.ufba.br/ri/handle/ri/10555}\n}\n\n
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\n\n\n
\n Contorno é o perfil, desenho ou formato de um objeto. Em Música, contornos podem ser abstraídos de qualquer parâmetro, como altura, densidade, ritmo, timbre, e intensidade. O estudo de relações de contornos musicais é importante porque tais relações são facilmente reconhecíveis auditivamente por músicos e leigos, e porque, assim como conjuntos de notas e motivos, contornos podem ajudar a dar coerência a uma obra musical. A Teoria de Relações de Contornos Musicais foi desenvolvida por autores como Michael L. Friedmann, Robert D. Morris, e Elizabeth W. Marvin e Paul Laprade. Esta teoria fornece conceitos e operações que ajudam a dar precisão no estudo das relações de contornos musicais. Eu descobri que o algoritmo de forma prima de classes de contornos equivalentes de Marvin e Laprade é inconsistente. Baseado na inconsistência deste algoritmo, levantei duas hipóteses: a Teoria dos Contornos contém inconsistências em outros pontos além deste algoritmo; e a inconsistência deste algoritmo implica em erros nos desdobramentos e nos resultados das análises de obras musicais baseadas nesta teoria. Este trabalho teve duas partes. A primeira teve como objetivo principal verificar a existência de inconsistências na Teoria dos Contornos e propor soluções. A segunda teve como objetivo compor um grupo de composições com eventual uso de relações de contornos musicais. A metodologia de verificação de inconsistências consistiu no desenvolvimento do programa MusiContour e na realização de testes funcionais. Então, programei e testei um conjunto de 37 operações e conceitos da Teoria dos Contornos. Com a pesquisa que originou este trabalho pude verificar que a primeira hipótese, das inconsistências em outros pontos da Teoria dos Contornos, é verdadeira, e que a segunda hipótese, do impacto da inconsistência do algoritmo de Marvin e Laprade, é falsa. Os principais resultados deste trabalho são os novos algoritmos de forma prima de classes de contornos equivalentes e de redução de contornos, revisão de conceitos, operações, definição de novas operações, o programa MusiContour, a organização didática do texto sobre a teoria, e a composição e apresentação de sete obras musicais.\n
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\n \n\n \n \n \n \n \n Melodic similarity among folk songs: An annotation study on similarity-based categorization in music.\n \n \n \n\n\n \n Volk, A.; and van Kranenburg, P.\n\n\n \n\n\n\n Musicae Scientiae, 16(0): 317–339. 2012.\n \n\n\n\n
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@Article{          volk.ea2012-melodic,\n    author       = {Volk, Anja and van Kranenburg, Peter},\n    year         = {2012},\n    title        = {Melodic similarity among folk songs: An annotation study\n                   on similarity-based categorization in music},\n    doi          = {10.1177/1029864912448329},\n    issn         = {1029-8649},\n    journal      = {Musicae Scientiae},\n    keywords     = {categorization,melodic similarity,music\n                   similarity,musical features,tune families},\n    mendeley-tags= {music similarity},\n    number       = {0},\n    pages        = {317--339},\n    volume       = {16}\n}\n\n
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\n \n\n \n \n \n \n \n \n Feature-Based Analysis of Haydn String Quartets.\n \n \n \n \n\n\n \n Wong, L.\n\n\n \n\n\n\n 2012.\n \n\n\n\n
\n\n\n\n \n \n \"Feature-BasedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Misc{             wong2012-feature-based,\n    author       = {Wong, Lawson},\n    year         = {2012},\n    title        = {Feature-Based Analysis of Haydn String Quartets},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {1--11},\n    url          = {https://ocw.mit.edu/courses/music-and-theater-arts/21m-269-studies-in-western-music-history-quantitative-and-computational-approaches-to-music-history-spring-2012/assignments/MIT21M_269S12_assn_final1.pdf}\n}\n\n
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\n  \n 2011\n \n \n (11)\n \n \n
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\n \n\n \n \n \n \n \n \n Categorization of Tonal Music Style: A quantitative investigation.\n \n \n \n \n\n\n \n Bellmann, H. G.\n\n\n \n\n\n\n Ph.D. Thesis, Griffith University, 2011.\n \n\n\n\n
\n\n\n\n \n \n \"CategorizationPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@PhDThesis{        bellmann2011-categorization,\n    author       = {Bellmann, H{\\'{e}}ctor G.},\n    year         = {2011},\n    title        = {Categorization of Tonal Music Style: A quantitative\n                   investigation},\n    keywords     = {between-measures index,entropy,global average dot\n                   product,intermodal in- dex,key determination,modulation\n                   index,music analysis,music data mining,music pattern\n                   recognition,music stylometry,musicXML,musical style\n                   taxonomy,notation complexity,quantitative music\n                   research,rhythm pattern,style classification,style\n                   theory,tonal music style,within-measures index},\n    mendeley-tags= {music analysis},\n    number       = {December},\n    school       = {Griffith University},\n    type         = {Ph.D. Dissertation},\n    url          = {https://www120.secure.griffith.edu.au/rch/file/1cf4aba7-cf39-ef53-ec9e-4708168fd5ca/1/Bellmann_2012_02Thesis.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Stochastic processes and database-driven Musicology.\n \n \n \n \n\n\n \n Burgoyne, J. A.\n\n\n \n\n\n\n Ph.D. Thesis, McGill University, 2011.\n \n\n\n\n
\n\n\n\n \n \n \"StochasticPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@PhDThesis{        burgoyne2011-stochastic,\n    author       = {Burgoyne, John Ashley},\n    year         = {2011},\n    title        = {Stochastic processes and database-driven Musicology},\n    abstract     = {For more than a decade, music information science and\n                   musicology have been at what Nicholas Cook has described\n                   as a 'moment of opportunity' for collaboration on\n                   database-driven musicology. The literature contains\n                   relatively few examples of mathematical tools that are\n                   suitable for analysing temporally structured data like\n                   music, however, and there are surprisingly few large\n                   databases of music that contain information at the\n                   semantic levels of interest to musicologists. This\n                   dissertation compiles a bibliography of the most important\n                   concepts from probability and statistics for analysing\n                   musical data, reviews how previous researchers have used\n                   statistics to study temporal relationships in music, and\n                   presents a new corpus of carefully curated chord labels\n                   from more than 1000 popular songs from the latter half of\n                   the twentieth century, as ranked by Billboard magazine's\n                   Hot 100 chart. The corpus is based on a careful sampling\n                   methodology that maintained cost efficiency while ensuring\n                   that the corpus is well suited to drawing conclusions\n                   about how harmonic practises may have evolved over time\n                   and to what extent they may have affected songs'\n                   popularity. This dissertation also introduces techniques\n                   new to the musicological community for analysing databases\n                   of this size and scope, most importantly the\n                   Dirichlet-multinomial distribution and constraint-based\n                   structure learning for causal Bayesian networks. The\n                   analysis confirms some common intuitions about harmonic\n                   practises in popular music and suggests several intriguing\n                   directions for further research.},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    school       = {McGill University},\n    type         = {Ph.D. Thesis},\n    url          = {https://escholarship.mcgill.ca/concern/theses/d217qt98k?locale=en}\n}\n\n
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\n For more than a decade, music information science and musicology have been at what Nicholas Cook has described as a 'moment of opportunity' for collaboration on database-driven musicology. The literature contains relatively few examples of mathematical tools that are suitable for analysing temporally structured data like music, however, and there are surprisingly few large databases of music that contain information at the semantic levels of interest to musicologists. This dissertation compiles a bibliography of the most important concepts from probability and statistics for analysing musical data, reviews how previous researchers have used statistics to study temporal relationships in music, and presents a new corpus of carefully curated chord labels from more than 1000 popular songs from the latter half of the twentieth century, as ranked by Billboard magazine's Hot 100 chart. The corpus is based on a careful sampling methodology that maintained cost efficiency while ensuring that the corpus is well suited to drawing conclusions about how harmonic practises may have evolved over time and to what extent they may have affected songs' popularity. This dissertation also introduces techniques new to the musicological community for analysing databases of this size and scope, most importantly the Dirichlet-multinomial distribution and constraint-based structure learning for causal Bayesian networks. The analysis confirms some common intuitions about harmonic practises in popular music and suggests several intriguing directions for further research.\n
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\n \n\n \n \n \n \n \n True or False? Re-Assessing the Voice-Leading Role of Haydn's So-Called “False Recapitulations”.\n \n \n \n\n\n \n Burstein, L. P.\n\n\n \n\n\n\n Journal of Schenkerian Studies, 5: 1–37. 2011.\n \n\n\n\n
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@Article{          burstein2011-true,\n    author       = {Burstein, L. Poundie},\n    year         = {2011},\n    title        = {True or False? Re-Assessing the Voice-Leading Role of\n                   Haydn's So-Called “False Recapitulations”},\n    journal      = {Journal of Schenkerian Studies},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    pages        = {1--37},\n    volume       = {5}\n}\n\n
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\n \n\n \n \n \n \n \n Musical Style Identification Using Grammatical Inference: The Encoding Problem.\n \n \n \n\n\n \n Cruz-Alcázar, P. P.; Vidal-Ruiz, E.; and Pérez-Cortés, J. C.\n\n\n \n\n\n\n In Sanfeliu, A.; and Shulcloper, J. R., editor(s), Proc. Iberoamerican Congress on Pattern Recognition, pages 375–382, 2011. Springer Berlin Heidelberg\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    cruz-alcazar.ea2011-musical,\n    author       = {Cruz-Alc{\\'{a}}zar, Pedro P. and Vidal-Ruiz, Enrique and\n                   P{\\'{e}}rez-Cort{\\'{e}}s, Juan C.},\n    year         = {2011},\n    title        = {Musical Style Identification Using Grammatical Inference:\n                   The Encoding Problem},\n    abstract     = {Un modelo de estilo identificaci{\\'{o}}n musical basado\n                   en inferencia gramatical (GI) se presenta. Bajo este\n                   modelo, las gram{\\'{a}}ticas regulares se utilizan para\n                   modelar el estilo musical. Clasificaci{\\'{o}}n de estilo\n                   se puede utilizar para implementar o mejorar la\n                   recuperaci{\\'{o}}n de contenido basado en bases de datos\n                   multimedia, la musicolog{\\'{i}}a y educaci{\\'{o}}n\n                   musical. En este trabajo, varias t{\\'{e}}cnicas de GI se\n                   utilizan para aprender, a partir de ejemplos de\n                   melod{\\'{i}}as, una gram{\\'{a}}tica estoc{\\'{a}}stica para\n                   cada uno de los tres estilos musicales diferentes. Luego,\n                   cada una de las gram{\\'{a}}ticas aprendido proporciona un\n                   valor de confianza de una composici{\\'{o}}n que pertenece\n                   a la gram{\\'{a}}tica, que puede ser utilizado para\n                   clasificar las melod{\\'{i}}as de prueba. Una\n                   cuesti{\\'{o}}n muy importante en este caso es el uso de un\n                   esquema de codificaci{\\'{o}}n de la m{\\'{u}}sica adecuada,\n                   los sistemas de codificaci{\\'{o}}n que se presentan\n                   diferentes y en comparaci{\\'{o}}n, alcanzando una tasa de\n                   error de clasificaci{\\'{o}}n del 3%.ABSTRACTA Musical\n                   Style Identification model based on Grammatical Inference\n                   (GI) is presented. Under this model, regular grammars are\n                   used for modeling Musical Style. Style Classification can\n                   be used to implement or improve content based retrieval in\n                   multimedia databases, musicology or music education. In\n                   this work, several GI Techniques are used to learn, from\n                   examples of melodies, a stochastic grammar for each of\n                   three different musical styles. Then, each of the learned\n                   grammars provides a confidence value of a composition\n                   belonging to that grammar, which can be used to classify\n                   test melodies. A very important issue in this case is the\n                   use of a proper music coding scheme, so different coding\n                   schemes are presented and compared, achieving a 3 %\n                   classification error rate.},\n    booktitle    = {Proc. Iberoamerican Congress on Pattern Recognition},\n    doi          = {10.1007/978-3-540-24586-5_46},\n    editor       = {Sanfeliu, A. and Shulcloper, J. Ruiz-},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    pages        = {375--382},\n    publisher    = {Springer Berlin Heidelberg}\n}\n\n
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\n Un modelo de estilo identificación musical basado en inferencia gramatical (GI) se presenta. Bajo este modelo, las gramáticas regulares se utilizan para modelar el estilo musical. Clasificación de estilo se puede utilizar para implementar o mejorar la recuperación de contenido basado en bases de datos multimedia, la musicología y educación musical. En este trabajo, varias técnicas de GI se utilizan para aprender, a partir de ejemplos de melodías, una gramática estocástica para cada uno de los tres estilos musicales diferentes. Luego, cada una de las gramáticas aprendido proporciona un valor de confianza de una composición que pertenece a la gramática, que puede ser utilizado para clasificar las melodías de prueba. Una cuestión muy importante en este caso es el uso de un esquema de codificación de la música adecuada, los sistemas de codificación que se presentan diferentes y en comparación, alcanzando una tasa de error de clasificación del 3%.ABSTRACTA Musical Style Identification model based on Grammatical Inference (GI) is presented. Under this model, regular grammars are used for modeling Musical Style. Style Classification can be used to implement or improve content based retrieval in multimedia databases, musicology or music education. In this work, several GI Techniques are used to learn, from examples of melodies, a stochastic grammar for each of three different musical styles. Then, each of the learned grammars provides a confidence value of a composition belonging to that grammar, which can be used to classify test melodies. A very important issue in this case is the use of a proper music coding scheme, so different coding schemes are presented and compared, achieving a 3 % classification error rate.\n
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\n \n\n \n \n \n \n \n \n Feature Extraction and Machine Learning on Symbolic Music using the music21 Toolkit.\n \n \n \n \n\n\n \n Cuthbert, M. S.; Ariza, C.; and Friedland, L.\n\n\n \n\n\n\n In Proceedings of International Symposium on Music Information Retrieval, 2011. \n \n\n\n\n
\n\n\n\n \n \n \"FeaturePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@InProceedings{    cuthbert.ea2011-feature,\n    author       = {Cuthbert, Michael Scott and Ariza, Christopher and\n                   Friedland, Lisa},\n    year         = {2011},\n    title        = {Feature Extraction and Machine Learning on Symbolic Music\n                   using the music21 Toolkit},\n    booktitle    = {Proceedings of International Symposium on Music\n                   Information Retrieval},\n    url          = {http://ismir2011.ismir.net/papers/PS3-6.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n Blurring the Boundaries: Toward a Multivalent Reading of Three First-Movement Sonata Forms in Haydn's Op. 50 String Quartets.\n \n \n \n\n\n \n Duncan, S. P.\n\n\n \n\n\n\n Musicological Explorations, 12(0): 5–40. 2011.\n \n\n\n\n
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@Article{          duncan2011-blurring,\n    author       = {Duncan, Stuart Paul},\n    year         = {2011},\n    title        = {Blurring the Boundaries: Toward a Multivalent Reading of\n                   Three First-Movement Sonata Forms in Haydn's Op. 50 String\n                   Quartets},\n    issn         = {1711-9235},\n    journal      = {Musicological Explorations},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {0},\n    pages        = {5--40},\n    volume       = {12}\n}\n\n
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\n \n\n \n \n \n \n \n Mozart's Viennese instrumental music: A study of stylistic re-invention.\n \n \n \n\n\n \n Keefe, S. P.\n\n\n \n\n\n\n Boydell Press, Woodbridge, 2011.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             keefe2011-mozarts,\n    author       = {Keefe, Simon P.},\n    year         = {2011},\n    title        = {Mozart's Viennese instrumental music: A study of\n                   stylistic re-invention},\n    address      = {Woodbridge},\n    isbn         = {9781843833192},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    pages        = {1--217},\n    publisher    = {Boydell Press}\n}\n\n
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\n \n\n \n \n \n \n \n \n Joseph Haydn's “witty” play on Hepokoski and Darcy's Elements of Sonata Theory. James Hepokoski/Warren Darcy, Elements of Sonata Theory: Norms, Types, and Deformations in the Late-Eighteenth-Century Sonata, New York: Oxford University Press 2006.\n \n \n \n \n\n\n \n Neuwirth, M.\n\n\n \n\n\n\n Zeitschrift der Gesellschaft für Musiktheorie [Journal of the German-Speaking Society of Music Theory], 8(1): 199–220. 2011.\n \n\n\n\n
\n\n\n\n \n \n \"JosephPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          neuwirth2011-joseph,\n    author       = {Neuwirth, Markus},\n    year         = {2011},\n    title        = {Joseph Haydn's “witty” play on Hepokoski and Darcy's\n                   Elements of Sonata Theory. James Hepokoski/Warren Darcy,\n                   Elements of Sonata Theory: Norms, Types, and Deformations\n                   in the Late-Eighteenth-Century Sonata, New York: Oxford\n                   University Press 2006.},\n    abstract     = {This paper presents a detailed integration process for\n                   XML schemata\\ncalled BInXS. BInXS adopts a global-as-view\n                   integration approach\\nthat builds a global schema from a\n                   set of heterogeneous XML schemata\\nrelated to a same\n                   application domain. This bottom-up approach maps\\nall\n                   element and attribute definitions in XML schemata to\n                   correspondent\\nconcepts at the global schema, allowing\n                   access to all data available\\nat the XML sources. The\n                   integration process is semi-automatically\\nperformed over\n                   conceptual representations of the XML schemata,\n                   which\\nprovides a better understanding of the semantics of\n                   the XML data\\nto be unified. A conceptual schema is\n                   generated by a set of conversion\\nrules that are applied\n                   to a schema definition for XML data. Once\\nthis conceptual\n                   schema is the result of a meticulous analysis of\\nthe XML\n                   logical model, it is able to abstract the\n                   particularities\\nof semistructured and XML data, like\n                   elements with mixed contents\\nand elements with\n                   alternative representations. Therefore, the\n                   further\\nunification of such conceptual schemata\n                   implicitly deals with structural\\nconflicts inherent to\n                   semistructured and XML data. In addition, BInXS\\nsupports\n                   a mapping strategy based on XPath expressions in order\n                   to\\nmaintain correspondences among global concepts and\n                   data at the XML\\nsources.},\n    doi          = {10.31751/586},\n    issn         = {1862-6742},\n    journal      = {Zeitschrift der Gesellschaft f{\\"{u}}r Musiktheorie\n                   [Journal of the German-Speaking Society of Music Theory]},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {1},\n    pages        = {199--220},\n    url          = {https://www.gmth.de/zeitschrift/artikel/586.aspx},\n    volume       = {8}\n}\n\n
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\n This paper presents a detailed integration process for XML schemata\\ncalled BInXS. BInXS adopts a global-as-view integration approach\\nthat builds a global schema from a set of heterogeneous XML schemata\\nrelated to a same application domain. This bottom-up approach maps\\nall element and attribute definitions in XML schemata to correspondent\\nconcepts at the global schema, allowing access to all data available\\nat the XML sources. The integration process is semi-automatically\\nperformed over conceptual representations of the XML schemata, which\\nprovides a better understanding of the semantics of the XML data\\nto be unified. A conceptual schema is generated by a set of conversion\\nrules that are applied to a schema definition for XML data. Once\\nthis conceptual schema is the result of a meticulous analysis of\\nthe XML logical model, it is able to abstract the particularities\\nof semistructured and XML data, like elements with mixed contents\\nand elements with alternative representations. Therefore, the furtherνnification of such conceptual schemata implicitly deals with structural\\nconflicts inherent to semistructured and XML data. In addition, BInXS\\nsupports a mapping strategy based on XPath expressions in order to\\nmaintain correspondences among global concepts and data at the XML\\nsources.\n
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\n \n\n \n \n \n \n \n Haydn's Missing Middles.\n \n \n \n\n\n \n Riley, M.\n\n\n \n\n\n\n Music Analysis, 30(1): 37–57. 2011.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          riley2011-haydns,\n    author       = {Riley, Matthew},\n    year         = {2011},\n    title        = {Haydn's Missing Middles},\n    abstract     = {Haydn's play on expectations and conventions and his\n                   deliberate grammatical mistakes are well-known. Yet one\n                   notable syntactic irregularity to be found in his music\n                   has been overlooked: the use of a sentential theme which\n                   lacks the first half of the continuation phrase (to use\n                   the terms of William E. Caplin's functional theory of\n                   Classical form). This type of theme moves straight from\n                   its presentation phrase to its cadential progression, so\n                   there is no pre-cadential section of the continuation\n                   phrase which expresses a specifically medial function.\n                   Moreover, the theme's dimensions are irregular: its second\n                   part is only half the length of its first. Most cases of\n                   the 'missing middle' occur in the main themes of sonata\n                   allegros, the middle being supplied later in the movement,\n                   usually in the subordinate theme. These points are\n                   illustrated by brief analyses of the first movements of\n                   Symphony No. 85 and the Sonata Hob. XVI:21, and a longer\n                   analysis of the first movement of the Sonata Hob. XVI:49.\n                   {\\textcopyright} 2011 The Author. Music Analysis\n                   {\\textcopyright} 2011 Blackwell Publishing Ltd.},\n    doi          = {10.1111/j.1468-2249.2011.00309.x},\n    issn         = {02625245},\n    journal      = {Music Analysis},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {37--57},\n    volume       = {30}\n}\n\n
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\n Haydn's play on expectations and conventions and his deliberate grammatical mistakes are well-known. Yet one notable syntactic irregularity to be found in his music has been overlooked: the use of a sentential theme which lacks the first half of the continuation phrase (to use the terms of William E. Caplin's functional theory of Classical form). This type of theme moves straight from its presentation phrase to its cadential progression, so there is no pre-cadential section of the continuation phrase which expresses a specifically medial function. Moreover, the theme's dimensions are irregular: its second part is only half the length of its first. Most cases of the 'missing middle' occur in the main themes of sonata allegros, the middle being supplied later in the movement, usually in the subordinate theme. These points are illustrated by brief analyses of the first movements of Symphony No. 85 and the Sonata Hob. XVI:21, and a longer analysis of the first movement of the Sonata Hob. XVI:49. © 2011 The Author. Music Analysis © 2011 Blackwell Publishing Ltd.\n
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\n \n\n \n \n \n \n \n \n Computational Methods for the Analysis of Musical Structure.\n \n \n \n \n\n\n \n Sapp, C. S.\n\n\n \n\n\n\n Ph.D. Thesis, Stanford University, 2011.\n \n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@PhDThesis{        sapp2011-computational,\n    author       = {Sapp, Craig Stuart},\n    year         = {2011},\n    title        = {Computational Methods for the Analysis of Musical\n                   Structure},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    school       = {Stanford University},\n    type         = {Ph.D. Dissertation},\n    url          = {https://stacks.stanford.edu/file/druid:br237mp4161/dissertation-submitted-augmented.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Unfolding the potential of computational musicology.\n \n \n \n \n\n\n \n Volk, A.; Wiering, F.; and Kranenburg, P. V.\n\n\n \n\n\n\n Proceedings of the13th International Conference on Informatics and Semiotics in Organisations (ICISO),137–144. 2011.\n \n\n\n\n
\n\n\n\n \n \n \"UnfoldingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          volk.ea2011-unfolding,\n    author       = {Volk, Anja and Wiering, Frans and Kranenburg, Peter Van},\n    year         = {2011},\n    title        = {Unfolding the potential of computational musicology},\n    journal      = {Proceedings of the13th International Conference on\n                   Informatics and Semiotics in Organisations (ICISO)},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {137--144},\n    url          = {http://www.cs.uu.nl/groups/MG/multimedia/publications/art/CompMus_Volketal.pdf}\n}\n\n
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\n  \n 2010\n \n \n (13)\n \n \n
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\n \n\n \n \n \n \n \n \n Melodic Accent as an Emergent Property of Tonal Motion.\n \n \n \n \n\n\n \n Ammirante, P.; and Thompson, W. F.\n\n\n \n\n\n\n Empirical Musicology Review, 5(3): 94–107. 2010.\n \n\n\n\n
\n\n\n\n \n \n \"MelodicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          ammirante.ea2010-melodic,\n    author       = {Ammirante, Paolo and Thompson, William Forde},\n    year         = {2010},\n    title        = {Melodic Accent as an Emergent Property of Tonal Motion},\n    abstract     = {In a previous continuation tapping study (Ammirante,\n                   Thompson, \\& Russo, in press), each tap triggered a\n                   discrete tone in a sequence randomly varying in pitch\n                   height and contour. Although participants were instructed\n                   to ignore the tones, pitch distance and pitch contour\n                   influenced intertap interval (ITI) and tap velocity (TV).\n                   The current study replicated these findings with original\n                   melodies. Results were interpreted as an effect of\n                   apparent tonal motion, with deviation in ITI and TV\n                   mirroring implied tonal acceleration. Due to overlapping\n                   perceptual and motor representations, participants may\n                   have failed to disambiguate acceleration implied by tonal\n                   motion from the acceleration of their finger trajectory.\n                   Dissociative effects of pitch distance on ITI and pitch\n                   contour on TV implied that pitch distance influences the\n                   initial finger extension while pitch contour influences\n                   later finger flexion. Acceleration in ITI and TV were also\n                   both correlated with melodic accent strength values from\n                   perceptual data (Thomassen, 1982), suggesting that\n                   perception and production of melodic accent emerge from\n                   shared action associations.},\n    doi          = {10.18061/1811/47559},\n    issn         = {1559-5749},\n    journal      = {Empirical Musicology Review},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {3},\n    pages        = {94--107},\n    url          = {https://kb.osu.edu/handle/1811/47559},\n    volume       = {5}\n}\n\n
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\n In a previous continuation tapping study (Ammirante, Thompson, & Russo, in press), each tap triggered a discrete tone in a sequence randomly varying in pitch height and contour. Although participants were instructed to ignore the tones, pitch distance and pitch contour influenced intertap interval (ITI) and tap velocity (TV). The current study replicated these findings with original melodies. Results were interpreted as an effect of apparent tonal motion, with deviation in ITI and TV mirroring implied tonal acceleration. Due to overlapping perceptual and motor representations, participants may have failed to disambiguate acceleration implied by tonal motion from the acceleration of their finger trajectory. Dissociative effects of pitch distance on ITI and pitch contour on TV implied that pitch distance influences the initial finger extension while pitch contour influences later finger flexion. Acceleration in ITI and TV were also both correlated with melodic accent strength values from perceptual data (Thomassen, 1982), suggesting that perception and production of melodic accent emerge from shared action associations.\n
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\n \n\n \n \n \n \n \n \n Polyphony as a loosening technique in Mozart's Haydn quartets.\n \n \n \n \n\n\n \n Bakulina, O.\n\n\n \n\n\n\n Ph.D. Thesis, McGill University, 2010.\n \n\n\n\n
\n\n\n\n \n \n \"PolyphonyPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@PhDThesis{        bakulina2010-polyphony,\n    author       = {Bakulina, Olga},\n    year         = {2010},\n    title        = {Polyphony as a loosening technique in Mozart's Haydn\n                   quartets},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    school       = {McGill University},\n    type         = {MA Thesis},\n    url          = {http://digitool.library.mcgill.ca/webclient/StreamGate?folder_id=0&dvs=1459686324642$\\sim$853}\n}\n\n
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\n \n\n \n \n \n \n \n Mid-section cadences in Haydn's sonata-form movements.\n \n \n \n\n\n \n Burstein, L. P.\n\n\n \n\n\n\n Studia Musicologica, 51(1-2): 91–107. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          burstein2010-mid-section,\n    author       = {Burstein, L. Poundie},\n    year         = {2010},\n    title        = {Mid-section cadences in Haydn's sonata-form movements},\n    doi          = {10.1556/SMus.51.2010.1-2.7},\n    issn         = {00393266},\n    journal      = {Studia Musicologica},\n    keywords     = {Heinrich christoph koch,Joseph\n                   haydn,Sonata-form,Third-level default medial caesura,music\n                   analysis},\n    mendeley-tags= {music analysis},\n    number       = {1-2},\n    pages        = {91--107},\n    volume       = {51}\n}\n\n
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\n \n\n \n \n \n \n \n \n Musical Form, Forms & Formenlehre: Three Methodological Reflections.\n \n \n \n \n\n\n \n Caplin, W. E.; Hepokoski, J. A.; and Webster, J.\n\n\n \n\n\n\n Leuven University Press, Leuven, Belgium, 2 edition, 2010.\n \n\n\n\n
\n\n\n\n \n \n \"MusicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             caplin.ea2010-musical,\n    author       = {Caplin, William Earl and Hepokoski, James A. and Webster,\n                   James},\n    year         = {2010},\n    title        = {Musical Form, Forms \\& Formenlehre: Three Methodological\n                   Reflections},\n    abstract     = {In Musical Form, Forms, and Formenlehre, three eminent\n                   music theorists reflect on the fundamentals of "musical\n                   form." They discuss how to analyze form in music and\n                   question the relevance of analytical theories and methods\n                   in general. They illustrate their basic concepts andc\n                   oncerns by offering some concrete analyses of works by\n                   Mozart (Idomeneo Overture, Jupiter Symphony) and Beethoven\n                   (First and Pastoral Symphony, Egmont Overture, and Die\n                   Ruinen von Athen Overture).The volume is divided into\n                   three parts, focusing on Caplin's "theory of formal\n                   functions," Hepokoski's concept of "dialogic form," and\n                   Webster's method of "multivalent analysis" respectively.\n                   Each part begins with a basic essay by one of the three\n                   authors. Subsequently, the two opposing authors comment on\n                   issues and analyses they consider to be problematic or\n                   underdeveloped, in a style that ranges from the gently\n                   critical to the overtly polemical. Finally, the author of\n                   the initial essay is given the opportunity to reply to the\n                   comments, and to further refine his own fundamental ideas\n                   on musical form.},\n    address      = {Leuven, Belgium},\n    edition      = {2},\n    isbn         = {9789058678225},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    pages        = {179},\n    publisher    = {Leuven University Press},\n    url          = {https://books.google.com/books?id=YhAgAJDAK9sC&pgis=1}\n}\n\n
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\n In Musical Form, Forms, and Formenlehre, three eminent music theorists reflect on the fundamentals of \"musical form.\" They discuss how to analyze form in music and question the relevance of analytical theories and methods in general. They illustrate their basic concepts andc oncerns by offering some concrete analyses of works by Mozart (Idomeneo Overture, Jupiter Symphony) and Beethoven (First and Pastoral Symphony, Egmont Overture, and Die Ruinen von Athen Overture).The volume is divided into three parts, focusing on Caplin's \"theory of formal functions,\" Hepokoski's concept of \"dialogic form,\" and Webster's method of \"multivalent analysis\" respectively. Each part begins with a basic essay by one of the three authors. Subsequently, the two opposing authors comment on issues and analyses they consider to be problematic or underdeveloped, in a style that ranges from the gently critical to the overtly polemical. Finally, the author of the initial essay is given the opportunity to reply to the comments, and to further refine his own fundamental ideas on musical form.\n
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\n \n\n \n \n \n \n \n \n Discovery of distinctive patterns in music.\n \n \n \n \n\n\n \n Conklin, D.\n\n\n \n\n\n\n Intelligent Data Analysis, 14(5): 547–554. sep 2010.\n \n\n\n\n
\n\n\n\n \n \n \"DiscoveryPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          conklin2010-discovery,\n    author       = {Conklin, Darrell},\n    year         = {2010},\n    title        = {Discovery of distinctive patterns in music},\n    abstract     = {This paper proposes a new view of pattern discovery in\n                   music: inductive querying a corpus for maximally general\n                   distinctive patterns. A pattern is distinctive if it is\n                   over-represented with respect to an anticorpus, and\n                   maximally general distinctive if no subsuming pattern is\n                   also distinctive. An algorithm for maximally general\n                   distinctive pattern discovery is presented and applied to\n                   folk song melodies from three geographic regions, and to\n                   chord sequences from three music genres. Distinctive\n                   patterns are applicable to a wide range of music analysis\n                   tasks where an anticorpus can be defined and contrasted\n                   with an analysis corpus. {\\textcopyright} 2010 - IOS Press\n                   and the authors. All rights reserved.},\n    doi          = {10.3233/IDA-2010-0438},\n    editor       = {Conklin, Darrell and Anagnostopoulou, Christina and\n                   Ramirez, Rafael},\n    issn         = {15714128},\n    journal      = {Intelligent Data Analysis},\n    keywords     = {Pattern discovery,anticorpus,chord sequences,computer and\n                   music,distinctive pattern,folk songs,subsumption},\n    mendeley-tags= {computer and music},\n    month        = {sep},\n    number       = {5},\n    pages        = {547--554},\n    url          = {https://www.medra.org/servlet/aliasResolver?alias=iospress&doi=10.3233/IDA-2010-0438},\n    volume       = {14}\n}\n\n
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\n This paper proposes a new view of pattern discovery in music: inductive querying a corpus for maximally general distinctive patterns. A pattern is distinctive if it is over-represented with respect to an anticorpus, and maximally general distinctive if no subsuming pattern is also distinctive. An algorithm for maximally general distinctive pattern discovery is presented and applied to folk song melodies from three geographic regions, and to chord sequences from three music genres. Distinctive patterns are applicable to a wide range of music analysis tasks where an anticorpus can be defined and contrasted with an analysis corpus. © 2010 - IOS Press and the authors. All rights reserved.\n
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\n \n\n \n \n \n \n \n \n Music21 A Toolkit for Computer-Aided Musicology and Symbolic Music Data.\n \n \n \n \n\n\n \n Cuthbert, M. S.; and Ariza, C.\n\n\n \n\n\n\n In Proceedings of International Symposium on Music Information Retrieval, pages 637–642, 2010. \n \n\n\n\n
\n\n\n\n \n \n \"Music21Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@InProceedings{    cuthbert.ea2010-music21,\n    author       = {Cuthbert, Michael Scott and Ariza, Christopher},\n    year         = {2010},\n    title        = {Music21 A Toolkit for Computer-Aided Musicology and\n                   Symbolic Music Data},\n    booktitle    = {Proceedings of International Symposium on Music\n                   Information Retrieval},\n    keywords     = {music visualization,p1},\n    mendeley-tags= {music visualization,p1},\n    pages        = {637--642},\n    url          = {http://ismir2010.ismir.net/proceedings/ismir2010-108.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n The Reinstatement of Polyphony in Musical Construction: Fugal Finales in Haydn's Op. 20 String Quartets.\n \n \n \n\n\n \n Grier, J.\n\n\n \n\n\n\n The Journal of Musicology, 27(1): 55–83. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          grier2010-reinstatement,\n    author       = {Grier, James},\n    year         = {2010},\n    title        = {The Reinstatement of Polyphony in Musical Construction:\n                   Fugal Finales in Haydn's Op. 20 String Quartets},\n    doi          = {10.1525/jm.2010.27.1.55.JM2701},\n    journal      = {The Journal of Musicology},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1},\n    pages        = {55--83},\n    volume       = {27}\n}\n\n
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\n \n\n \n \n \n \n \n \n Towards automatic extraction of harmony information from music signals.\n \n \n \n \n\n\n \n Harte, C.\n\n\n \n\n\n\n Ph.D. Thesis, Queen Mary, University of London, 2010.\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@PhDThesis{        harte2010-towards,\n    author       = {Harte, Christopher},\n    year         = {2010},\n    title        = {Towards automatic extraction of harmony information from\n                   music signals},\n    keywords     = {Electronic Engineering,computer and music},\n    mendeley-tags= {computer and music},\n    school       = {Queen Mary, University of London},\n    type         = {Ph.D. Dissertation},\n    url          = {http://qmro.qmul.ac.uk/jspui/handle/123456789/534}\n}\n\n
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\n \n\n \n \n \n \n \n \n Characterisation of composer style using high-level musical features.\n \n \n \n \n\n\n \n Mearns, L.; Tidhar, D.; and Dixon, S.\n\n\n \n\n\n\n Proceedings of 3rd international workshop on Machine learning and music - MML '10,37. 2010.\n \n\n\n\n
\n\n\n\n \n \n \"CharacterisationPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          mearns.ea2010-characterisation,\n    author       = {Mearns, Lesley and Tidhar, Dan and Dixon, Simon},\n    year         = {2010},\n    title        = {Characterisation of composer style using high-level\n                   musical features},\n    address      = {New York, New York, USA},\n    doi          = {10.1145/1878003.1878016},\n    isbn         = {9781450301619},\n    journal      = {Proceedings of 3rd international workshop on Machine\n                   learning and music - MML '10},\n    keywords     = {computer and music,counterpoint,machine\n                   learning,music,style},\n    mendeley-tags= {computer and music},\n    pages        = {37},\n    publisher    = {ACM Press},\n    url          = {http://portal.acm.org/citation.cfm?doid=1878003.1878016}\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n Does a 'monothematic' expositional design have tautological implications for the recapitulation? An alternative approach to 'altered recapitulations' in Haydn.\n \n \n \n\n\n \n Neuwirth, M.\n\n\n \n\n\n\n Studia Musicologica, 51(3-4): 369–385. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          neuwirth2010-does,\n    author       = {Neuwirth, Markus},\n    year         = {2010},\n    title        = {Does a 'monothematic' expositional design have\n                   tautological implications for the recapitulation? An\n                   alternative approach to 'altered recapitulations' in\n                   Haydn},\n    abstract     = {'Altered recapitulations,' commonly regarded as a\n                   distinguishing feature of Joseph Haydn's sonata form\n                   movements, are usually explained in terms of the\n                   'monothematic' design of the exposition. According to the\n                   logic used in such analytical studies, recomposing the\n                   recapitulation would have been aimed at restoring the\n                   proportional balance between exposition and\n                   recapitulation, a need that resulted from the omission of\n                   the seemingly redundant, retransposed secondary theme\n                   along with the preceding transition. Though such an\n                   explanation has long been considered indisputable, this\n                   article casts doubt on the validity of the redundancy\n                   principle by showing that Haydn often did retain the\n                   monothematic section in the recapitulation. Rather, the\n                   recomposition of the recapitulation results from two\n                   important structural aspects thus far largely neglected in\n                   the literature: (1) the repetitive formal structure of the\n                   main theme, which is often considerably reworked in the\n                   recapitulation; and (2) the insertion of a separate newly\n                   composed dominant zone in the recapitulation that serves\n                   to compensate for the lack of a structural dominant at the\n                   end of the development section. Finally, it is argued here\n                   that Haydn, who was deeply rooted in the late Baroque\n                   tradition, by no means regarded multiple 'double returns'\n                   as either problematic or redundant, for he may have been\n                   thinking more in terms of an overriding ritornello\n                   structure.},\n    doi          = {10.1556/SMus.51.2010.3-4.9},\n    issn         = {00393266},\n    journal      = {Studia Musicologica},\n    keywords     = {Joseph Haydn,monothematic exposition,music\n                   analysis,recomposed recapitulation,ritornello\n                   principle,sonata form},\n    mendeley-tags= {music analysis},\n    number       = {3-4},\n    pages        = {369--385},\n    volume       = {51}\n}\n\n
\n
\n\n\n
\n 'Altered recapitulations,' commonly regarded as a distinguishing feature of Joseph Haydn's sonata form movements, are usually explained in terms of the 'monothematic' design of the exposition. According to the logic used in such analytical studies, recomposing the recapitulation would have been aimed at restoring the proportional balance between exposition and recapitulation, a need that resulted from the omission of the seemingly redundant, retransposed secondary theme along with the preceding transition. Though such an explanation has long been considered indisputable, this article casts doubt on the validity of the redundancy principle by showing that Haydn often did retain the monothematic section in the recapitulation. Rather, the recomposition of the recapitulation results from two important structural aspects thus far largely neglected in the literature: (1) the repetitive formal structure of the main theme, which is often considerably reworked in the recapitulation; and (2) the insertion of a separate newly composed dominant zone in the recapitulation that serves to compensate for the lack of a structural dominant at the end of the development section. Finally, it is argued here that Haydn, who was deeply rooted in the late Baroque tradition, by no means regarded multiple 'double returns' as either problematic or redundant, for he may have been thinking more in terms of an overriding ritornello structure.\n
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\n\n\n
\n \n\n \n \n \n \n \n Artificial Intelligence: A Modern Approach.\n \n \n \n\n\n \n Russel, S. J.; and Norvig, P.\n\n\n \n\n\n\n Pearson, Boston, 3 edition, 2010.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Book{             russel.ea2010-artificial,\n    author       = {Russel, Stuart J. and Norvig, Peter},\n    year         = {2010},\n    title        = {Artificial Intelligence: A Modern Approach},\n    address      = {Boston},\n    publisher    = {Pearson},\n    edition      = {3}\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Melodic Contour Similarity Using Folk Melodies.\n \n \n \n \n\n\n \n Schmuckler, M. A.\n\n\n \n\n\n\n Music Perception, 28(2): 169–194. 2010.\n \n\n\n\n
\n\n\n\n \n \n \"MelodicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@Article{          schmuckler2010-melodic,\n    author       = {Schmuckler, Mark A.},\n    year         = {2010},\n    title        = {Melodic Contour Similarity Using Folk Melodies},\n    issn         = {0730-7829},\n    journal      = {Music Perception},\n    keywords     = {music contour,music similarity},\n    mendeley-tags= {music contour,music similarity},\n    number       = {2},\n    pages        = {169--194},\n    publisher    = {JSTOR},\n    url          = {http://www.jstor.org/stable/10.1525/mp.2010.28.2.169},\n    volume       = {28}\n}\n\n
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\n \n\n \n \n \n \n \n Applying subgroup discovery for the analysis of string quartet movements.\n \n \n \n\n\n \n Taminau, J.; Hillewaere, R.; Meganck, S.; Conklin, D.; Nowé, A.; and Manderick, B.\n\n\n \n\n\n\n MML'10 - Proceedings of the 3rd ACM International Workshop on Machine Learning and Music, Co-located with ACM Multimedia 2010, (May 2014): 29–32. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          taminau.ea2010-applying,\n    author       = {Taminau, Jonatan and Hillewaere, Ruben and Meganck, Stijn\n                   and Conklin, Darrell and Now{\\'{e}}, Ann and Manderick,\n                   Bernard},\n    year         = {2010},\n    title        = {Applying subgroup discovery for the analysis of string\n                   quartet movements},\n    abstract     = {Descriptive and predictive analyses of symbolic music\n                   data assist in understanding the properties that\n                   characterize specific genres, movements and composers.\n                   Subgroup Discovery, a machine learning technique lying on\n                   the intersection between these types of analysis, is\n                   applied on a dataset of string quartet movements composed\n                   by either Haydn or Mozart. The resulting rules describe\n                   subgroups of movements for each composer, which are\n                   examined manually, and we investigate whether these\n                   subgroups correlate with metadata such as type of movement\n                   or period. In addition to this descriptive analysis, the\n                   obtained rules are used for the predictive task of\n                   composer classification; results are compared with\n                   previous results on this corpus.},\n    doi          = {10.1145/1878003.1878014},\n    isbn         = {9781450301619},\n    journal      = {MML'10 - Proceedings of the 3rd ACM International\n                   Workshop on Machine Learning and Music, Co-located with\n                   ACM Multimedia 2010},\n    keywords     = {Global features,Subgroup discovery,computational\n                   musicology},\n    mendeley-tags= {computational musicology},\n    number       = {May 2014},\n    pages        = {29--32}\n}\n\n
\n
\n\n\n
\n Descriptive and predictive analyses of symbolic music data assist in understanding the properties that characterize specific genres, movements and composers. Subgroup Discovery, a machine learning technique lying on the intersection between these types of analysis, is applied on a dataset of string quartet movements composed by either Haydn or Mozart. The resulting rules describe subgroups of movements for each composer, which are examined manually, and we investigate whether these subgroups correlate with metadata such as type of movement or period. In addition to this descriptive analysis, the obtained rules are used for the predictive task of composer classification; results are compared with previous results on this corpus.\n
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\n  \n 2009\n \n \n (10)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Contour reduction algorithms: a theory of pitch and duration hierarchies for post-tonal music.\n \n \n \n \n\n\n \n Bor, M.\n\n\n \n\n\n\n Ph.D. Thesis, University of British Columbia, 2009.\n \n\n\n\n
\n\n\n\n \n \n \"ContourPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        bor2009-contour,\n    author       = {Bor, Mustafa},\n    year         = {2009},\n    title        = {Contour reduction algorithms: a theory of pitch and\n                   duration hierarchies for post-tonal music},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    number       = {April},\n    publisher    = {University of British Columbia},\n    school       = {University of British Columbia},\n    type         = {PhD Dissertation},\n    url          = {http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:CONTOUR+REDUCTION+ALGORITHMS+:+A+THEORY+OF+PITCH+AND+DURATION+HIERARCHIES+FOR+POST-TONAL+MUSIC#0}\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Anomaly detection: A Survey.\n \n \n \n \n\n\n \n Chandola, V.; Banerjee, A.; and Kumar, V.\n\n\n \n\n\n\n ACM Computing Surveys, 41(3): 1–58. jul 2009.\n \n\n\n\n
\n\n\n\n \n \n \"AnomalyPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          chandola.ea2009-anomaly,\n    author       = {Chandola, Varun and Banerjee, Arindam and Kumar, Vipin},\n    year         = {2009},\n    title        = {Anomaly detection: A Survey},\n    abstract     = {The paper presents a revolutionary framework for the\n                   modeling, detection, characterization, identification, and\n                   machine-learning of anomalous behavior in observed\n                   phenomena arising from a large class of unknown and\n                   uncertain dynamical systems. An evolved behavior would in\n                   general be very difficult to correct unless the specific\n                   anomalous event that caused such behavior can be detected\n                   early, and any consequence attributed to the specific\n                   anomaly following its detection. Substantial investigative\n                   time and effort is required to back-track the cause for\n                   abnormal behavior and to recreate the event sequence\n                   leading to such abnormal behavior. The need to\n                   automatically detect anomalous behavior is therefore\n                   critical using principles of state motion, and to do so\n                   with a human operator in the loop. Human-machine\n                   interaction results in a capability for machine\n                   self-learning and in producing a robust decision-support\n                   mechanism. This is the fundamental concept of intelligent\n                   control wherein machine-learning is enhanced by\n                   interaction with human operators. Copyright\n                   {\\textcopyright} 2009 Tech Science Press.},\n    doi          = {10.1145/1541880.1541882},\n    issn         = {0360-0300},\n    journal      = {ACM Computing Surveys},\n    keywords     = {Anomaly detection,Decision-making,Machine\n                   intelligence,Nonlinear dynamical\n                   systems,Soft-computing,statistics},\n    mendeley-tags= {statistics},\n    month        = {jul},\n    number       = {3},\n    pages        = {1--58},\n    url          = {https://dl.acm.org/doi/10.1145/1541880.1541882},\n    volume       = {41}\n}\n\n
\n
\n\n\n
\n The paper presents a revolutionary framework for the modeling, detection, characterization, identification, and machine-learning of anomalous behavior in observed phenomena arising from a large class of unknown and uncertain dynamical systems. An evolved behavior would in general be very difficult to correct unless the specific anomalous event that caused such behavior can be detected early, and any consequence attributed to the specific anomaly following its detection. Substantial investigative time and effort is required to back-track the cause for abnormal behavior and to recreate the event sequence leading to such abnormal behavior. The need to automatically detect anomalous behavior is therefore critical using principles of state motion, and to do so with a human operator in the loop. Human-machine interaction results in a capability for machine self-learning and in producing a robust decision-support mechanism. This is the fundamental concept of intelligent control wherein machine-learning is enhanced by interaction with human operators. Copyright © 2009 Tech Science Press.\n
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\n \n\n \n \n \n \n \n The string quartet.\n \n \n \n\n\n \n Eisen, C.\n\n\n \n\n\n\n In The Cambridge History of Eighteenth-Century Music, pages 648–660. Cambridge University Press, Cambridge, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InCollection{     eisen2009-string,\n    author       = {Eisen, Cliff},\n    year         = {2009},\n    title        = {The string quartet},\n    address      = {Cambridge},\n    language     = {English},\n    booktitle    = {The {Cambridge} {History} of {Eighteenth}-{Century}\n                   {Music}},\n    publisher    = {Cambridge University Press},\n    pages        = {648--660}\n}\n\n
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\n \n\n \n \n \n \n \n Análise particional: uma mediação entre composição musical e a teoria das partições.\n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n Ph.D. Thesis, Universidade Federal do Rio de Janeiro, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        gentil-nunes2009-analise,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2009},\n    title        = {An{\\'{a}}lise particional: uma media{\\c{c}}{\\~{a}}o entre\n                   composi{\\c{c}}{\\~{a}}o musical e a teoria das\n                   parti{\\c{c}}{\\~{o}}es},\n    keywords     = {music composition},\n    mendeley-tags= {music composition},\n    school       = {Universidade Federal do Rio de Janeiro},\n    type         = {Ph.D. Dissertation}\n}\n\n
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\n \n\n \n \n \n \n \n The Cambridge History of Eighteenth-Century Music.\n \n \n \n\n\n \n Keefe, S. P.,\n editor.\n \n\n\n \n\n\n\n Cambridge University Press, Cambridge, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             keefe2009-cambridge,\n    year         = {2009},\n    title        = {The Cambridge History of Eighteenth-Century Music},\n    address      = {Cambridge},\n    editor       = {Keefe, Simon P.},\n    isbn         = {9780521663199},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Cambridge University Press}\n}\n\n
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\n \n\n \n \n \n \n \n Metric Manipulations in Haydn and Mozart: Chamber Music for Strings, 1787-1791.\n \n \n \n\n\n \n Mirka, D.\n\n\n \n\n\n\n Oxford University Press, Oxford, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             mirka2009-metric,\n    author       = {Mirka, Danuta},\n    year         = {2009},\n    title        = {Metric Manipulations in Haydn and Mozart: Chamber Music\n                   for Strings, 1787-1791},\n    address      = {Oxford},\n    isbn         = {9788578110796},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Oxford University Press}\n}\n\n
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\n \n\n \n \n \n \n \n \n Is Music Structure Annotation Multi-Dimensional? A Proposal for Robust Local Music Annotation .\n \n \n \n \n\n\n \n Peeters, G.; and Deruty, E.\n\n\n \n\n\n\n In Baumann, S.; Burred, J. J.; Nürnberger, A.; and Stober, S., editor(s), Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS), pages 75–90, Graz, Austria, 2009. \n \n\n\n\n
\n\n\n\n \n \n \"IsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    peeters.ea2009-is,\n    author       = {Peeters, Geoffroy and Deruty, Emmanuel},\n    year         = {2009},\n    title        = {Is Music Structure Annotation Multi-Dimensional? A\n                   Proposal for Robust Local Music Annotation .},\n    address      = {Graz, Austria},\n    booktitle    = {Proceedings of the 3rd Workshop on Learning the Semantics\n                   of Audio Signals (LSAS)},\n    editor       = {Baumann, Stephan and Burred, Juan Jos{\\'{e}} and\n                   N{\\"{u}}rnberger, Andreas and Stober, Sebastian},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    pages        = {75--90},\n    url          = {http://lsas2009.dke-research.de/proceedings/lsas2009peetersDeruty.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n A diachronic-transformational theory of musical contour relations.\n \n \n \n\n\n \n Schultz, R. D.\n\n\n \n\n\n\n Ph.D. Thesis, University of Washington, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        schultz2009-diachronic-transformational,\n    author       = {Schultz, Rob D.},\n    year         = {2009},\n    title        = {A diachronic-transformational theory of musical contour\n                   relations},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    school       = {University of Washington},\n    type         = {PhD Dissertation}\n}\n\n
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\n \n\n \n \n \n \n \n Before the joke: Texture and sociability in the Largo of Haydn's op. 33, no. 2.\n \n \n \n\n\n \n Sutcliffe, W. D.\n\n\n \n\n\n\n Journal of Musicological Research, 28(2-3): 92–118. 2009.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          sutcliffe2009-before,\n    author       = {Sutcliffe, W. Dean},\n    year         = {2009},\n    title        = {Before the joke: Texture and sociability in the Largo of\n                   Haydn's op. 33, no. 2},\n    abstract     = {The Largo e sostenuto of Haydn's string quartet Op. 33,\n                   No. 2, embodies various forms of sociable interaction.\n                   This entails transactions between thematic materials as\n                   well as the four players themselves, and involves the\n                   imaginative handling of formula as well as the\n                   foregrounding of composer-listener relationships through\n                   overt manipulation and disruption. This movement, as well\n                   as the remarkable finale to which it leads, is also placed\n                   within the wider context of a later-eighteenth-century\n                   aesthetic of sociability. Copyright {\\textcopyright}\n                   Taylor \\& Francis Group, LLC.},\n    doi          = {10.1080/01411890902922470},\n    issn         = {01411896},\n    journal      = {Journal of Musicological Research},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {2-3},\n    pages        = {92--118},\n    volume       = {28}\n}\n\n
\n
\n\n\n
\n The Largo e sostenuto of Haydn's string quartet Op. 33, No. 2, embodies various forms of sociable interaction. This entails transactions between thematic materials as well as the four players themselves, and involves the imaginative handling of formula as well as the foregrounding of composer-listener relationships through overt manipulation and disruption. This movement, as well as the remarkable finale to which it leads, is also placed within the wider context of a later-eighteenth-century aesthetic of sociability. Copyright © Taylor & Francis Group, LLC.\n
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\n \n\n \n \n \n \n \n Python 3 Reference Manual.\n \n \n \n\n\n \n Van Rossum, G.; and Drake, F. L.\n\n\n \n\n\n\n CreateSpace, Scotts Valley, CA, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Book{             van-rossum.ea2009-python,\n    author       = {Van Rossum, Guido and Drake, Fred L.},\n    year         = {2009},\n    title        = {Python 3 Reference Manual},\n    isbn         = {1441412697},\n    publisher    = {CreateSpace},\n    address      = {Scotts Valley, CA}\n}\n\n
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\n  \n 2008\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n \n Centrality and Distribution of Partitions according to the Transfer Distance.\n \n \n \n \n\n\n \n Belgacem, L.; and Hudry, O.\n\n\n \n\n\n\n In DIMACS/LAMSADE Workshop on Algorithmic Decision Theory and Meeting of the COST Action ICO602, Paris, 2008. \n \n\n\n\n
\n\n\n\n \n \n \"CentralityPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@InProceedings{    belgacem.ea2008-centrality,\n    author       = {Belgacem, Lucile and Hudry, Olivier},\n    year         = {2008},\n    title        = {Centrality and Distribution of Partitions according to\n                   the Transfer Distance},\n    address      = {Paris},\n    booktitle    = {DIMACS/LAMSADE Workshop on Algorithmic Decision Theory\n                   and Meeting of the COST Action ICO602},\n    keywords     = {centrality,clustering,distance,mathematics,partition,transfer\n                   graph},\n    mendeley-tags= {mathematics},\n    url          = {http://archive.dimacs.rutgers.edu/Workshops/DecisionTheory3/Belgacem_Hudry.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n A musicologia enquanto método científico.\n \n \n \n \n\n\n \n Castagna, P.\n\n\n \n\n\n\n Revista do Conservatório Brasileiro de Pelotas, (1): 7–31. 2008.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          castagna2008-musicologia,\n    author       = {Castagna, Paulo},\n    year         = {2008},\n    title        = {A musicologia enquanto m{\\'{e}}todo cient{\\'{i}}fico},\n    abstract     = {Resultado da reuni{\\~{a}}o de v{\\'{a}}rias atividades\n                   ligadas ao estudo te{\\'{o}}rico da m{\\'{u}}sica a partir\n                   do s{\\'{e}}culo XVII, apesar de ra{\\'{i}}zes que remontam\n                   {\\`{a}} Antiguidade, a musicologia surgiu como o estudo\n                   cient{\\'{i}}fico ou acad{\\^{e}}mico da m{\\'{u}}sica,\n                   particularmente no {\\^{a}}mbito do positivismo de Auguste\n                   Comte (1798-1857), diferenciando-se, assim, da abordagem\n                   da m{\\'{u}}sica dependente da pr{\\'{a}}tica art{\\'{i}}stica.},\n    journal      = {Revista do Conservat{\\'{o}}rio Brasileiro de Pelotas},\n    keywords     = {musicology},\n    mendeley-tags= {musicology},\n    number       = {1},\n    pages        = {7--31},\n    url          = {https://periodicos.ufpel.edu.br/ojs2/index.php/RCM/article/view/2430/2281}\n}\n\n
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\n\n\n
\n Resultado da reunião de várias atividades ligadas ao estudo teórico da música a partir do século XVII, apesar de raízes que remontam à Antiguidade, a musicologia surgiu como o estudo científico ou acadêmico da música, particularmente no âmbito do positivismo de Auguste Comte (1798-1857), diferenciando-se, assim, da abordagem da música dependente da prática artística.\n
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\n \n\n \n \n \n \n \n Mozart, Haydn and Early Beethoven 1781-1802.\n \n \n \n\n\n \n Heartz, D.\n\n\n \n\n\n\n W. W. Norton & Company, New York and London, 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             heartz2008-mozart,\n    author       = {Heartz, Daniel},\n    year         = {2008},\n    title        = {Mozart, Haydn and Early Beethoven 1781-1802},\n    address      = {New York and London},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
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\n \n\n \n \n \n \n \n Instrumental arias or sonic tableaux: 'Voice' in Haydn's string quartets Opp. 9 and 17.\n \n \n \n\n\n \n November, N.\n\n\n \n\n\n\n Music and Letters, 89(3): 346–372. 2008.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          november2008-instrumental,\n    author       = {November, Nancy},\n    year         = {2008},\n    title        = {Instrumental arias or sonic tableaux: 'Voice' in Haydn's\n                   string quartets Opp. 9 and 17},\n    abstract     = {The reception of Haydns early string quartets is\n                   chequered. Professional performers tend to avoid the\n                   quartets before Op. 20 (1772). In scholarship, essential\n                   features of 'Classical' string quartets are typically\n                   thought to be in place at the earliest with Op. 20, but\n                   more usually with Op. 33. This essay contributes to a\n                   critique of these assumptions, and offers an alternative\n                   view of the earlier works. The slow movements in\n                   particular, with their solo 'arias' for first violin, have\n                   been considered especially problematic. From a historical\n                   perspective, however, these movements can be understood to\n                   exemplify a fundamentally new mode of expression that was\n                   extolled by mid-eighteenth-century theorists: that of the\n                   tableau. This concept was discussed, for example, by\n                   Jean-Jacques Rousseau and Denis Diderot, and was brought\n                   to the stages of Vienna and Eszterhza in the ballets of\n                   Jean-Georges Noverre and the operas of Gluck and Haydn,\n                   among others. As sonic tableaux, or instrumental 'arias',\n                   movements from Haydns early string quartets epitomize a\n                   dramatic mode that was of fundamental importance to music\n                   of the Classical era.},\n    doi          = {10.1093/ml/gcm130},\n    issn         = {00274224},\n    journal      = {Music and Letters},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {3},\n    pages        = {346--372},\n    volume       = {89}\n}\n\n
\n
\n\n\n
\n The reception of Haydns early string quartets is chequered. Professional performers tend to avoid the quartets before Op. 20 (1772). In scholarship, essential features of 'Classical' string quartets are typically thought to be in place at the earliest with Op. 20, but more usually with Op. 33. This essay contributes to a critique of these assumptions, and offers an alternative view of the earlier works. The slow movements in particular, with their solo 'arias' for first violin, have been considered especially problematic. From a historical perspective, however, these movements can be understood to exemplify a fundamentally new mode of expression that was extolled by mid-eighteenth-century theorists: that of the tableau. This concept was discussed, for example, by Jean-Jacques Rousseau and Denis Diderot, and was brought to the stages of Vienna and Eszterhza in the ballets of Jean-Georges Noverre and the operas of Gluck and Haydn, among others. As sonic tableaux, or instrumental 'arias', movements from Haydns early string quartets epitomize a dramatic mode that was of fundamental importance to music of the Classical era.\n
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\n \n\n \n \n \n \n \n A manual annotation method for melodic similarity and the study of melody feature sets.\n \n \n \n\n\n \n Volk, A.; van Kranenburg, P.; Garbers, J.; Wiering, F.; Veltkamp, R. C; and Grijp, L. P\n\n\n \n\n\n\n In Proceedings of the International Conference on Music Information Retrieval (ISMIR), pages 101–106, 2008. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    volk.ea2008-manual,\n    author       = {Volk, Anja and van Kranenburg, Peter and Garbers,\n                   J{\\"{o}}rg and Wiering, Frans and Veltkamp, Remco C and\n                   Grijp, Louis P},\n    year         = {2008},\n    title        = {A manual annotation method for melodic similarity and the\n                   study of melody feature sets},\n    booktitle    = {Proceedings of the International Conference on Music\n                   Information Retrieval (ISMIR)},\n    keywords     = {music similarity},\n    mendeley-tags= {music similarity},\n    pages        = {101--106}\n}\n\n
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\n \n\n \n \n \n \n \n Music in the Galant Style.\n \n \n \n\n\n \n Gjerdingen, R. O.\n\n\n \n\n\n\n Oxford University Press, New York, 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             gjerdingen2007-music,\n    author       = {Gjerdingen, Robert O.},\n    year         = {2007},\n    title        = {Music in the Galant Style},\n    address      = {New York},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    publisher    = {Oxford University Press}\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Applied Multivariate Statistical Analysis.\n \n \n \n \n\n\n \n Johnson, R. A.; and Wichern, D. W.\n\n\n \n\n\n\n Pearson Prentice Hall, Upper Saddle River, New Jersey, 6 edition, 2007.\n \n\n\n\n
\n\n\n\n \n \n \"AppliedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             johnson.ea2007-applied,\n    author       = {Johnson, Richard A. and Wichern, Dean W.},\n    year         = {2007},\n    title        = {Applied Multivariate Statistical Analysis},\n    address      = {Upper Saddle River, New Jersey},\n    edition      = {6},\n    isbn         = {9780131877153},\n    keywords     = {mathematics},\n    mendeley-tags= {mathematics},\n    publisher    = {Pearson Prentice Hall},\n    url          = {http://cisco.qu.edu.qa/artssciences/mathphysta/stats/syllabi/Syllabus-\n                   spring\n                   2012/Statistics/Dr_Alodat_STAT_459_L01_Spring_2012.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Style-independent computer-assisted exploratory analysis of large music collections.\n \n \n \n \n\n\n \n McKay, C.; and Fujinaga, I.\n\n\n \n\n\n\n Journal of Interdisciplinary Music Studies, 1(1): 63–85. 2007.\n \n\n\n\n
\n\n\n\n \n \n \"Style-independentPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          mckay.ea2007-style-independent,\n    author       = {McKay, Cory and Fujinaga, Ichiro},\n    year         = {2007},\n    title        = {Style-independent computer-assisted exploratory analysis\n                   of large music collections},\n    abstract     = {The first goal of this paper is to introduce musi-\n                   cologists and music theorists to the benefits of- fered by\n                   state-of-the-art pattern recognition tech- niques. The\n                   second goal is to provide them with a computer-based\n                   framework that can be used to study large and diverse\n                   collections of music for the purposes of empirically\n                   developing, explor- ing and validating theoretical models.\n                   The soft- ware presented in this paper implements tech-\n                   niques from the fields of machine learning, pat- tern\n                   recognition and data mining applied to and considered from\n                   the perspectives of music theory and musicology.},\n    doi          = {10.1.1.149.7958},\n    journal      = {Journal of Interdisciplinary Music Studies},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    number       = {1},\n    pages        = {63--85},\n    url          = {http://www.musicstudies.org/spring2007.html},\n    volume       = {1}\n}\n\n
\n
\n\n\n
\n The first goal of this paper is to introduce musi- cologists and music theorists to the benefits of- fered by state-of-the-art pattern recognition tech- niques. The second goal is to provide them with a computer-based framework that can be used to study large and diverse collections of music for the purposes of empirically developing, explor- ing and validating theoretical models. The soft- ware presented in this paper implements tech- niques from the fields of machine learning, pat- tern recognition and data mining applied to and considered from the perspectives of music theory and musicology.\n
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\n \n\n \n \n \n \n \n \n Register in Haydn's String Quartets: Four Case Studies.\n \n \n \n \n\n\n \n November, N.\n\n\n \n\n\n\n Music Analysis, 26(3): 289–322. oct 2007.\n \n\n\n\n
\n\n\n\n \n \n \"RegisterPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          november2007-register,\n    author       = {November, Nancy},\n    year         = {2007},\n    title        = {Register in Haydn's String Quartets: Four Case Studies},\n    doi          = {10.1111/j.1468-2249.2008.00260.x},\n    issn         = {02625245},\n    journal      = {Music Analysis},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    month        = {oct},\n    number       = {3},\n    pages        = {289--322},\n    url          = {http://doi.wiley.com/10.1111/j.1468-2249.2008.00260.x},\n    volume       = {26}\n}\n\n
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\n \n\n \n \n \n \n \n Statistical modeling and retrieval of polyphonic music.\n \n \n \n\n\n \n Unal, E.; Georgiou, P. G.; Narayanan, S. S.; and Chew, E.\n\n\n \n\n\n\n In 2007 IEEE 9Th International Workshop on Multimedia Signal Processing, MMSP 2007 - Proceedings, pages 405–409, Crete, 2007. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    unal.ea2007-statistical,\n    author       = {Unal, Erdem and Georgiou, Panayiotis G. and Narayanan,\n                   Shrikanth S. and Chew, Elaine},\n    year         = {2007},\n    title        = {Statistical modeling and retrieval of polyphonic music},\n    abstract     = {AbstractIn this article, we propose a solution to the\n                   problem of query by example for polyphonic music audio.We\n                   first present a generic mid-level representation for audio\n                   queries. Unlike previous efforts in the literature, the\n                   proposed representation is not dependent on the different\n                   spectral characteristics of different musical instruments\n                   and the accurate location of note onsets and offsets. This\n                   is achieved by first mapping the short term frequency\n                   spectrum of consecutive audio frames to the musical space\n                   (The Spiral Array) and defining a tonal identity with\n                   respect to center of effect that is generated by the\n                   spectral weights of the musical notes. We then use the\n                   resulting single dimensional text representations of the\n                   audio to create n-gram statistical sequence models to\n                   track the tonal characteristics and the behavior of the\n                   pieces. After performing appropriate smoothing, we build a\n                   collection of melodic n-gram models for testing. Using\n                   perplexity-based scoring, we test the likelihood of a\n                   sequence of lexical chords (an audio query) given each\n                   model in the database collection. Initial results show\n                   that, some variations of the input piece appears in the\n                   top 5 results 81pct of the time for whole melody inputs\n                   within a 500 polyphonic melody database. We also tested\n                   the retrieval engine for small audio clips. Using 25s\n                   segments, variations of the input piece are among the top\n                   5 results 75pct of the time.},\n    address      = {Crete},\n    booktitle    = {2007 IEEE 9Th International Workshop on Multimedia Signal\n                   Processing, MMSP 2007 - Proceedings},\n    doi          = {10.1109/MMSP.2007.4412902},\n    isbn         = {1424412749},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    number       = {November},\n    pages        = {405--409}\n}\n\n
\n
\n\n\n
\n AbstractIn this article, we propose a solution to the problem of query by example for polyphonic music audio.We first present a generic mid-level representation for audio queries. Unlike previous efforts in the literature, the proposed representation is not dependent on the different spectral characteristics of different musical instruments and the accurate location of note onsets and offsets. This is achieved by first mapping the short term frequency spectrum of consecutive audio frames to the musical space (The Spiral Array) and defining a tonal identity with respect to center of effect that is generated by the spectral weights of the musical notes. We then use the resulting single dimensional text representations of the audio to create n-gram statistical sequence models to track the tonal characteristics and the behavior of the pieces. After performing appropriate smoothing, we build a collection of melodic n-gram models for testing. Using perplexity-based scoring, we test the likelihood of a sequence of lexical chords (an audio query) given each model in the database collection. Initial results show that, some variations of the input piece appears in the top 5 results 81pct of the time for whole melody inputs within a 500 polyphonic melody database. We also tested the retrieval engine for small audio clips. Using 25s segments, variations of the input piece are among the top 5 results 75pct of the time.\n
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\n  \n 2006\n \n \n (9)\n \n \n
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\n \n\n \n \n \n \n \n \n Interestingness measures for data mining: A Survey.\n \n \n \n \n\n\n \n Geng, L.; and Hamilton, H. J.\n\n\n \n\n\n\n ACM Computing Surveys, 38(3): 9. sep 2006.\n \n\n\n\n
\n\n\n\n \n \n \"InterestingnessPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          geng.ea2006-interestingness,\n    author       = {Geng, Liqiang and Hamilton, Howard J.},\n    year         = {2006},\n    title        = {Interestingness measures for data mining: A Survey},\n    abstract     = {Interestingness measures play an important role in data\n                   mining, regardless of the kind of patterns being mined.\n                   These measures are intended for selecting and ranking\n                   patterns according to their potential interest to the\n                   user. Good measures also allow the time and space costs of\n                   the mining process to be reduced. This survey reviews the\n                   interestingness measures for rules and summaries,\n                   classifies them from several perspectives, compares their\n                   properties, identifies their roles in the data mining\n                   process, gives strategies for selecting appropriate\n                   measures for applications, and identifies opportunities\n                   for future research in this area. {\\textcopyright} 2006\n                   ACM.},\n    doi          = {10.1145/1132960.1132963},\n    issn         = {0360-0300},\n    journal      = {ACM Computing Surveys},\n    keywords     = {Association rules,Classification rules,Interest\n                   measures,Interestingness measures,Knowledge\n                   discovery,Summaries,computer},\n    mendeley-tags= {computer},\n    month        = {sep},\n    number       = {3},\n    pages        = {9},\n    url          = {https://dl.acm.org/doi/10.1145/1132960.1132963},\n    volume       = {38}\n}\n\n
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\n Interestingness measures play an important role in data mining, regardless of the kind of patterns being mined. These measures are intended for selecting and ranking patterns according to their potential interest to the user. Good measures also allow the time and space costs of the mining process to be reduced. This survey reviews the interestingness measures for rules and summaries, classifies them from several perspectives, compares their properties, identifies their roles in the data mining process, gives strategies for selecting appropriate measures for applications, and identifies opportunities for future research in this area. © 2006 ACM.\n
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\n \n\n \n \n \n \n \n \n Parsemas e o método de Fux.\n \n \n \n \n\n\n \n Gentil-Nunes, P.\n\n\n \n\n\n\n Revista Pesquisa e Música, 1: 38–47. 2006.\n \n\n\n\n
\n\n\n\n \n \n \"ParsemasPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          gentil-nunes2006-parsemas,\n    author       = {Gentil-Nunes, Pauxy},\n    year         = {2006},\n    title        = {Parsemas e o m{\\'{e}}todo de Fux},\n    journal      = {Revista Pesquisa e M{\\'{u}}sica},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    pages        = {38--47},\n    url          = {https://www.academia.edu/34020077/GENTIL_NUNES_Pauxy_Parsemas_e_o_m{\\'{e}}todo_de_Fux_In_Revista_Pesquisa_e_M{\\'{u}}sica_Rio_de_Janeiro_Conservat{\\'{o}}rio_Brasileiro_de_M{\\'{u}}sica_2006b_v_1_p_38_47},\n    volume       = {1}\n}\n\n
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\n \n\n \n \n \n \n \n The String Quartets of Joseph Haydn.\n \n \n \n\n\n \n Grave, F. K.; and Grave, M.\n\n\n \n\n\n\n Oxford University Press, New York, NY, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             grave.ea2006-string,\n    author       = {Grave, Floyd K. and Grave, Margaret},\n    year         = {2006},\n    title        = {The String Quartets of Joseph Haydn},\n    address      = {New York, NY},\n    doi          = {10.2307/831027},\n    issn         = {00030139},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Oxford University Press}\n}\n\n
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\n \n\n \n \n \n \n \n Elements of Sonata Theory: Norms, Types and Deformations in the Late-Eighteenth-Century Sonata.\n \n \n \n\n\n \n Hepokoski, J. A.; and Darcy, W.\n\n\n \n\n\n\n Oxford University Press, Oxford, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             hepokoski.ea2006-elements,\n    author       = {Hepokoski, James A. and Darcy, Warren},\n    year         = {2006},\n    title        = {Elements of Sonata Theory: Norms, Types and Deformations\n                   in the Late-Eighteenth-Century Sonata},\n    abstract     = {This book analyses the sonata. Both building on and\n                   departing from earlier methods of analysis, it provides an\n                   in-depth examination of the sonata genre. After\n                   establishing the normative features of the sonata, the\n                   authors examine how individual sonatas from Beethoven,\n                   Haydn, and Mozart both adhere to and deviate from those\n                   standards to a variety of effects. Co-authored by a music\n                   theorist and a musicologist, the book provides a\n                   foundational theory and offers insights on individual\n                   works from the Western canon.},\n    address      = {Oxford},\n    doi          = {10.1093/acprof:oso/9780195146400.001.0001},\n    isbn         = {9780195146400},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {Oxford University Press}\n}\n\n
\n
\n\n\n
\n This book analyses the sonata. Both building on and departing from earlier methods of analysis, it provides an in-depth examination of the sonata genre. After establishing the normative features of the sonata, the authors examine how individual sonatas from Beethoven, Haydn, and Mozart both adhere to and deviate from those standards to a variety of effects. Co-authored by a music theorist and a musicologist, the book provides a foundational theory and offers insights on individual works from the Western canon.\n
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\n \n\n \n \n \n \n \n Extended upbeats in the classical minuet: Interactions with hypermeter and phrase structure.\n \n \n \n\n\n \n McClelland, R.\n\n\n \n\n\n\n Music Theory Spectrum, 28(1): 23–56. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Article{          mcclelland2006-extended,\n    author       = {McClelland, Ryan},\n    year         = {2006},\n    title        = {Extended upbeats in the classical minuet: Interactions\n                   with hypermeter and phrase structure},\n    abstract     = {This article considers the hypermetric properties of\n                   minuets that begin with an upbeat gesture that spans at\n                   least one measure. Analyses of several minuets by Haydn\n                   and Mozart, and a quasi-minuet movement by Brahms,\n                   demonstrate five types of interaction between the extended\n                   upbeat and hypermeter. The analyses describe the evolving\n                   hypermetric structure of the minuets' openings and the\n                   subsequent development of this thematic material. The\n                   extended upbeat emerges in these minuets as a key\n                   compositional element with implications for expressive\n                   meaning and performance. {\\textcopyright} 2006 by The\n                   Society for Music Theory. All rights reserved.},\n    doi          = {10.1525/mts.2006.28.1.23},\n    issn         = {01956167},\n    journal      = {Music Theory Spectrum},\n    keywords     = {Anacrusis,Haydn,Hypermeter,Minuet,Upbeat,music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {23--56},\n    volume       = {28}\n}\n\n
\n
\n\n\n
\n This article considers the hypermetric properties of minuets that begin with an upbeat gesture that spans at least one measure. Analyses of several minuets by Haydn and Mozart, and a quasi-minuet movement by Brahms, demonstrate five types of interaction between the extended upbeat and hypermeter. The analyses describe the evolving hypermetric structure of the minuets' openings and the subsequent development of this thematic material. The extended upbeat emerges in these minuets as a key compositional element with implications for expressive meaning and performance. © 2006 by The Society for Music Theory. All rights reserved.\n
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\n \n\n \n \n \n \n \n Peak Experience High Register and Structure in the “Razumovsky” Quartets, Op. 59.\n \n \n \n\n\n \n Miller, M.\n\n\n \n\n\n\n In Kinderman, W., editor(s), The String Quartets of Beethoven, 3. University of Illinois Press, Urbana and Chicago, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     miller2006-peak,\n    author       = {Miller, Malcolm},\n    year         = {2006},\n    title        = {Peak Experience High Register and Structure in the\n                   “Razumovsky” Quartets, Op. 59},\n    address      = {Urbana and Chicago},\n    booktitle    = {The String Quartets of Beethoven},\n    chapter      = {3},\n    editor       = {Kinderman, William},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    publisher    = {University of Illinois Press}\n}\n\n
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\n \n\n \n \n \n \n \n Analise de Séries temporais.\n \n \n \n\n\n \n Morettin, P. A.; and Toloi, C. M. C.\n\n\n \n\n\n\n Edgard Blucher, São Paulo, 2 edition, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             morettin.ea2006-analise,\n    author       = {Morettin, Pedro A. and Toloi, Cl{\\'{e}}lia M. C.},\n    year         = {2006},\n    title        = {Analise de S{\\'{e}}ries temporais},\n    address      = {S{\\~{a}}o Paulo},\n    edition      = {2},\n    isbn         = {9788521203896},\n    keywords     = {statistics},\n    mendeley-tags= {statistics},\n    publisher    = {Edgard Blucher}\n}\n\n
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\n \n\n \n \n \n \n \n Cyclic Integration in the instrumental music of Haydn and Mozart.\n \n \n \n\n\n \n Proksch, B. J.\n\n\n \n\n\n\n Ph.D. Thesis, University of North Carolina at Chapel Hill, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        proksch2006-cyclic,\n    author       = {Proksch, Bryan Jeffrey},\n    year         = {2006},\n    title        = {Cyclic Integration in the instrumental music of Haydn and\n                   Mozart},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    school       = {University of North Carolina at Chapel Hill},\n    type         = {Ph.D. Dissertation}\n}\n\n
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\n \n\n \n \n \n \n \n Does melodic accent shape the melody contour in Estonian folk songs ?.\n \n \n \n\n\n \n Särg, T.\n\n\n \n\n\n\n In Proceedings of the 9th International Conference on Music Perception and Cognition (ICMPC-2006) and 6th Triennial Conference of the European Society for the Cognitive Sciences of Music (ESCOM), pages 1304–1309, Bologna, 2006. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n
@InProceedings{    sarg2006-does,\n    author       = {S{\\"{a}}rg, Taive},\n    year         = {2006},\n    title        = {Does melodic accent shape the melody contour in Estonian\n                   folk songs ?},\n    address      = {Bologna},\n    booktitle    = {Proceedings of the 9th International Conference on Music\n                   Perception and Cognition (ICMPC-2006) and 6th Triennial\n                   Conference of the European Society for the Cognitive\n                   Sciences of Music (ESCOM)},\n    keywords     = {melodic accent,melody variation,regilaul},\n    mendeley-tags= {melodic accent},\n    number       = {December},\n    pages        = {1304--1309}\n}\n\n
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\n  \n 2005\n \n \n (7)\n \n \n
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\n \n\n \n \n \n \n \n \n Regards on two regards by Messiaen: Post-tonal music segmentation using pitch context distances in the spiral array.\n \n \n \n \n\n\n \n Chew, E.\n\n\n \n\n\n\n Journal of New Music Research, 34(4): 341–354. dec 2005.\n \n\n\n\n
\n\n\n\n \n \n \"RegardsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          chew2005-regards,\n    author       = {Chew, Elaine},\n    year         = {2005},\n    title        = {Regards on two regards by Messiaen: Post-tonal music\n                   segmentation using pitch context distances in the spiral\n                   array},\n    abstract     = {This paper describes an O(n) algorithm for segmenting\n                   music automatically by pitch context using the Spiral\n                   Array, a mathematical model for tonality, and applies it\n                   to the segmentation of post-tonal music, namely, Olivier\n                   Messiaen's Regards IV and XVI from his Vingt Regards sur\n                   l'Enfant J{\\'{e}}sus . Using the idea of the centre of\n                   effect ( c.e .), a summary point in the interior of the\n                   Spiral Array, segmentation boundaries map to peaks in the\n                   distances between the c.e .'s of adjacent segments of\n                   music. The best-case computed boundaries are, on average,\n                   within 0.94% (for Regard IV ) and 0.11% (for Regard XVI )\n                   of their targets. {\\textcopyright} 2005 Taylor \\& Francis.},\n    doi          = {10.1080/09298210600578147},\n    issn         = {0929-8215},\n    journal      = {Journal of New Music Research},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    month        = {dec},\n    number       = {4},\n    pages        = {341--354},\n    url          = {http://www.tandfonline.com/doi/abs/10.1080/09298210600578147},\n    volume       = {34}\n}\n\n
\n
\n\n\n
\n This paper describes an O(n) algorithm for segmenting music automatically by pitch context using the Spiral Array, a mathematical model for tonality, and applies it to the segmentation of post-tonal music, namely, Olivier Messiaen's Regards IV and XVI from his Vingt Regards sur l'Enfant Jésus . Using the idea of the centre of effect ( c.e .), a summary point in the interior of the Spiral Array, segmentation boundaries map to peaks in the distances between the c.e .'s of adjacent segments of music. The best-case computed boundaries are, on average, within 0.94% (for Regard IV ) and 0.11% (for Regard XVI ) of their targets. © 2005 Taylor & Francis.\n
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\n \n\n \n \n \n \n \n \n Computational Musicology: An Artificial Life Approach.\n \n \n \n \n\n\n \n Coutinho, E.; Gimenes, M.; Martins, J. M.; and Miranda, E. R.\n\n\n \n\n\n\n In 2005 Portuguese Conference on Artificial Intelligence, pages 85–93, dec 2005. Ieee\n \n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InProceedings{    coutinho.ea2005-computational,\n    author       = {Coutinho, Eduardo and Gimenes, Marcelo and Martins, Joao\n                   M. and Miranda, Eduardo Reck},\n    year         = {2005},\n    title        = {Computational Musicology: An Artificial Life Approach},\n    booktitle    = {2005 Portuguese Conference on Artificial Intelligence},\n    doi          = {10.1109/EPIA.2005.341270},\n    isbn         = {0-7803-9365-1},\n    month        = {dec},\n    pages        = {85--93},\n    publisher    = {Ieee},\n    url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4145929}\n}\n\n
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\n \n\n \n \n \n \n \n \n Symbolic Representation Of Musical Chords: A Proposed Syntax For Text Annotations.\n \n \n \n \n\n\n \n Harte, C.; Sandler, M.; Abdallah, S.; and Gómez, E.\n\n\n \n\n\n\n In Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR 2005), pages 66–71, London, 2005. \n \n\n\n\n
\n\n\n\n \n \n \"SymbolicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    harte.ea2005-symbolic,\n    author       = {Harte, Cristopher and Sandler, Mark and Abdallah, Samer\n                   and G{\\'{o}}mez, Emilia},\n    year         = {2005},\n    title        = {Symbolic Representation Of Musical Chords: A Proposed\n                   Syntax For Text Annotations},\n    address      = {London},\n    booktitle    = {Proceedings of the 4th International Conference on Music\n                   Information Retrieval (ISMIR 2005)},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    pages        = {66--71},\n    url          = {http://en.scientificcommons.org/43256599}\n}\n\n
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\n \n\n \n \n \n \n \n Beethoven: The Music and the Life.\n \n \n \n\n\n \n Lockwood, L.\n\n\n \n\n\n\n W. W. Norton & Company, New York, 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             lockwood2005-beethoven,\n    author       = {Lockwood, Lewis},\n    year         = {2005},\n    title        = {Beethoven: The Music and the Life},\n    address      = {New York},\n    isbn         = {9780393326383},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
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\n \n\n \n \n \n \n \n \n The construction and evaluation of statistical models of melodic structure in music perception and composition.\n \n \n \n \n\n\n \n Pearce, M. T.\n\n\n \n\n\n\n Ph.D. Thesis, City University of London, 2005.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        pearce2005-construction,\n    author       = {Pearce, Marcus Thomas},\n    year         = {2005},\n    title        = {The construction and evaluation of statistical models of\n                   melodic structure in music perception and composition},\n    abstract     = {The prevalent approach to developing cognitive models of\n                   music perception and composition is to construct systems\n                   of symbolic rules and constraints on the basis of\n                   extensive music-theoretic and music-analytic knowledge.\n                   The thesis proposed in this dissertation is that\n                   statistical models which acquire knowledge through the\n                   induction of regularities in corpora of existing music\n                   can, if examined with appropriate methodologies, provide\n                   significant insights into the cognitive processing\n                   involved in music perception and composition. This claim\n                   is examined in three stages. First, a number of\n                   statistical modelling techniques drawn from the fields of\n                   data compression, statistical language modelling and\n                   machine learning are subjected to empirical evaluation in\n                   the context of sequential prediction of pitch structure in\n                   unseen melodies. This investigation results in a\n                   collection of modelling strategies which together yield\n                   significant performance improvements over existing\n                   methods. In the second stage, these statistical systems\n                   are used to examine observed patterns of expectation\n                   collected in previous psychological research on melody\n                   perception. In contrast to previous accounts of this data,\n                   the results demonstrate that these patterns of expectation\n                   can be accounted for in terms of the induction of\n                   statistical regularities acquired through exposure to\n                   music. In the final stage of the present research, the\n                   statistical systems developed in the first stage are used\n                   to examine the intrinsic computational demands of the task\n                   of composing a stylistically successful melody The results\n                   suggest that the systems lack the degree of expressive\n                   power needed to consistently meet the demands of the task.\n                   In contrast to previous research, however, the\n                   methodological framework developed for the evaluation of\n                   computational models of composition enables a detailed\n                   empirical examination and comparison of such models which\n                   facilitates the identification and resolution of their\n                   weaknesses.},\n    keywords     = {music analysis with computers},\n    mendeley-tags= {music analysis with computers},\n    school       = {City University of London},\n    type         = {Ph.D. Dissertation},\n    url          = {http://openaccess.city.ac.uk/id/eprint/8459/}\n}\n\n
\n
\n\n\n
\n The prevalent approach to developing cognitive models of music perception and composition is to construct systems of symbolic rules and constraints on the basis of extensive music-theoretic and music-analytic knowledge. The thesis proposed in this dissertation is that statistical models which acquire knowledge through the induction of regularities in corpora of existing music can, if examined with appropriate methodologies, provide significant insights into the cognitive processing involved in music perception and composition. This claim is examined in three stages. First, a number of statistical modelling techniques drawn from the fields of data compression, statistical language modelling and machine learning are subjected to empirical evaluation in the context of sequential prediction of pitch structure in unseen melodies. This investigation results in a collection of modelling strategies which together yield significant performance improvements over existing methods. In the second stage, these statistical systems are used to examine observed patterns of expectation collected in previous psychological research on melody perception. In contrast to previous accounts of this data, the results demonstrate that these patterns of expectation can be accounted for in terms of the induction of statistical regularities acquired through exposure to music. In the final stage of the present research, the statistical systems developed in the first stage are used to examine the intrinsic computational demands of the task of composing a stylistically successful melody The results suggest that the systems lack the degree of expressive power needed to consistently meet the demands of the task. In contrast to previous research, however, the methodological framework developed for the evaluation of computational models of composition enables a detailed empirical examination and comparison of such models which facilitates the identification and resolution of their weaknesses.\n
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\n \n\n \n \n \n \n \n Online database of scores in the Humdrum file format.\n \n \n \n\n\n \n Sapp, C. S.\n\n\n \n\n\n\n In Proc. 6th International Conference on Music Information Retrieval, pages 2, London, UK, 2005. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@InProceedings{    sapp2005-online,\n    author       = {Sapp, Craig Stuart},\n    year         = 2005,\n    title        = {Online database of scores in the {Humdrum} file format},\n    address      = {London, UK},\n    abstract     = {KernScores, an online library of musical data currently\n                   consisting of over 5 million notes, has been created to\n                   assist projects dealing with the computational analysis of\n                   musical scores. The online scores are in a format suitable\n                   for processing with the Humdrum Toolkit for Music\n                   Research, but the website also provides automatic\n                   translations into several other popular data formats for\n                   digital musical scores.},\n    language     = {en},\n    booktitle    = {Proc. 6th {International} {Conference} on {Music}\n                   {Information} {Retrieval}},\n    tags         = {computational musicology},\n    pages        = {2}\n}\n\n
\n
\n\n\n
\n KernScores, an online library of musical data currently consisting of over 5 million notes, has been created to assist projects dealing with the computational analysis of musical scores. The online scores are in a format suitable for processing with the Humdrum Toolkit for Music Research, but the website also provides automatic translations into several other popular data formats for digital musical scores.\n
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\n \n\n \n \n \n \n \n The problem of the 'Introduction' in Beethoven's late quartets.\n \n \n \n\n\n \n Taylor, B.\n\n\n \n\n\n\n Ad Parnassum, 3(6): 45–64. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          taylor2005-problem,\n    author       = {Taylor, Benedict},\n    year         = {2005},\n    title        = {The problem of the 'Introduction' in Beethoven's late\n                   quartets},\n    journal      = {Ad Parnassum},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {6},\n    pages        = {45--64},\n    volume       = {3}\n}\n\n
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\n  \n 2004\n \n \n (8)\n \n \n
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\n \n\n \n \n \n \n \n Integer Partitions.\n \n \n \n\n\n \n Andrews, G.; and Eriksson, K.\n\n\n \n\n\n\n Cambridge University Press, Cambridge, 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Book{             andrews.ea2004-integer,\n    author       = {Andrews, George and Eriksson, Kimmo},\n    year         = {2004},\n    title        = {Integer Partitions},\n    publisher    = {Cambridge University Press},\n    address      = {Cambridge}\n}\n\n
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\n \n\n \n \n \n \n \n \n Statistics in Musicology.\n \n \n \n \n\n\n \n Beran, J.\n\n\n \n\n\n\n Chapman & Hall/CRC, Boca Raton, Fla, 2004.\n \n\n\n\n
\n\n\n\n \n \n \"StatisticsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n
@Book{             beran2004-statistics,\n    author       = {Beran, Jan},\n    year         = {2004},\n    title        = {Statistics in Musicology},\n    address      = {Boca Raton, Fla},\n    isbn         = {1584882190},\n    keywords     = {Interdisciplinary statistics,Musical analysis-Statistical\n                   methods,music and mathematics},\n    mendeley-tags= {music and mathematics},\n    publisher    = {Chapman \\& Hall/CRC},\n    url          = {http://books.google.com/books?hl=en&lr=&id=ZRzoSDUvqOUC&oi=fnd&pg=PR7&dq=STATISTICS+in+MUSICOLOGY&ots=BWjT6F5UDG&sig=xD4FjAMo0NP1moxRraZ6Z1EQu8A}\n}\n\n
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\n \n\n \n \n \n \n \n \n The Classical Cadence: Conceptions and Misconceptions.\n \n \n \n \n\n\n \n Caplin, W. E.\n\n\n \n\n\n\n Journal of the American Musicological Society, 57(1): 51–118. 2004.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          caplin2004-classical,\n    author       = {Caplin, William Earl},\n    year         = {2004},\n    title        = {The Classical Cadence: Conceptions and Misconceptions},\n    abstract     = {The article examines notions traditionally attached to\n                   the concept of cadence in general, retains those features\n                   finding genuine expression in "the classical style" (as\n                   defined by the instrumental works of Haydn, Mozart, and\n                   Beethoven), and investigates problematic ideas that have\n                   the potential of producing theoretical and analytical\n                   confusion. It is argued that cadence effects formal\n                   closure only at middle-ground levels of structure; a\n                   cadential progression is highly constrained in its\n                   harmonic content; cadential function precedes the moment\n                   of cadential arrival, whereas the music following this\n                   arrival may be postcadential in function; cadential\n                   content must be distinguished from cadential function;\n                   cadence represents a formal end, not a rhythmic or\n                   textural stop; and cadential strength can be distinguished\n                   in its syntactical and rhetorical aspects. An analysis of\n                   selected musical passages demonstrates that an accurate\n                   identification of cadence has a major impact on the\n                   interpretation of musical form and phrase structure.},\n    doi          = {10.1525/jams.2004.57.1.51},\n    issn         = {00030139},\n    journal      = {Journal of the American Musicological Society},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {1},\n    pages        = {51--118},\n    url          = {https://jams.ucpress.edu/content/57/1/51},\n    volume       = {57}\n}\n\n
\n
\n\n\n
\n The article examines notions traditionally attached to the concept of cadence in general, retains those features finding genuine expression in \"the classical style\" (as defined by the instrumental works of Haydn, Mozart, and Beethoven), and investigates problematic ideas that have the potential of producing theoretical and analytical confusion. It is argued that cadence effects formal closure only at middle-ground levels of structure; a cadential progression is highly constrained in its harmonic content; cadential function precedes the moment of cadential arrival, whereas the music following this arrival may be postcadential in function; cadential content must be distinguished from cadential function; cadence represents a formal end, not a rhythmic or textural stop; and cadential strength can be distinguished in its syntactical and rhetorical aspects. An analysis of selected musical passages demonstrates that an accurate identification of cadence has a major impact on the interpretation of musical form and phrase structure.\n
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\n \n\n \n \n \n \n \n \n Computational and comparative musicology.\n \n \n \n \n\n\n \n Cook, N.\n\n\n \n\n\n\n In Clarke, E.; and Cook, N., editor(s), Empirical musicology: Aims, methods, prospects, 6, pages 103–126. Oxford University Press, 2004.\n \n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     cook2004-computational,\n    author       = {Cook, Nicholas},\n    year         = {2004},\n    title        = {Computational and comparative musicology},\n    booktitle    = {Empirical musicology: Aims, methods, prospects},\n    chapter      = {6},\n    editor       = {Clarke, Eric and Cook, Nicholas},\n    keywords     = {20: Western art music -- Musicology as discipline},\n    pages        = {103--126},\n    publisher    = {Oxford University Press},\n    url          = {http://search.ebscohost.com/login.aspx?direct=true&db=rih&AN=2004-11424&site=ehost-live}\n}\n\n
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\n \n\n \n \n \n \n \n \n Densidade e linearidade na configuração de texturas musicais.\n \n \n \n \n\n\n \n Gentil-Nunes, P.; and Carvalho, A.\n\n\n \n\n\n\n In Anais do 4° Colóquio de Pesquisa do PPGM-UFRJ, pages 40–49, Rio de Janeiro, 2004. \n \n\n\n\n
\n\n\n\n \n \n \"DensidadePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    gentil-nunes.ea2004-densidade,\n    author       = {Gentil-Nunes, Pauxy and Carvalho, Alexandre},\n    year         = {2004},\n    title        = {Densidade e linearidade na configura{\\c{c}}{\\~{a}}o de\n                   texturas musicais},\n    address      = {Rio de Janeiro},\n    booktitle    = {Anais do 4° Col{\\'{o}}quio de Pesquisa do PPGM-UFRJ},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    pages        = {40--49},\n    url          = {https://www.academia.edu/4393959/GENTIL_NUNES_Pauxy_e_CARVALHO_Alexandre_2003_Densidade_e_linearidade_na_configura{\\c{c}}{\\~{a}}o_de_texturas_musicais_In_Anais_do_IV_Col{\\'{o}}quio_de_Pesquisa_do_Programa_de_P{\\'{o}}s_Gradua{\\c{c}}{\\~{a}}o_da_Escola_de_M{\\'{u}}sica_da_UFRJ_Rio_de_Janeiro_UFRJ_2003}\n}\n\n
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\n \n\n \n \n \n \n \n Melodic Similarity: Looking for a Good Abstraction Level.\n \n \n \n\n\n \n Grachten, M.; Arcos, J. L.; and Mántaras, R. L. D.\n\n\n \n\n\n\n In Proceedings of the 5th International Society for Music Information Retrieval, 2004. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InProceedings{    grachten.ea2004-melodic,\n    author       = {Grachten, Maarten and Arcos, Josep Lluis and\n                   M{\\'{a}}ntaras, Ramon L{\\'{o}}pez De},\n    year         = {2004},\n    title        = {Melodic Similarity: Looking for a Good Abstraction\n                   Level},\n    abstract     = {Computing melodic similarity is a very general problem\n                   with diverse musical applications ranging from music\n                   analysis to content-based retrieval. Choosing the\n                   appropriate level of representation is a crucial issue and\n                   depends on the type of application. Our research interest\n                   concerns the development of a CBR system for expressive\n                   music processing. In that context, a well chosen distance\n                   measure for melodies is a crucial issue. In this paper we\n                   propose a new melodic similarity measure based on the I/R\n                   model for melodic structure and compare it with other\n                   existing measures. The experimentation shows that the\n                   proposed measure provides a good compromise between\n                   discriminatory power and ability to recognize phrases from\n                   the same song.},\n    booktitle    = {Proceedings of the 5th International Society for Music\n                   Information Retrieval},\n    isbn         = {84-88042-44-2},\n    keywords     = {music similarity},\n    mendeley-tags= {music similarity}\n}\n\n
\n
\n\n\n
\n Computing melodic similarity is a very general problem with diverse musical applications ranging from music analysis to content-based retrieval. Choosing the appropriate level of representation is a crucial issue and depends on the type of application. Our research interest concerns the development of a CBR system for expressive music processing. In that context, a well chosen distance measure for melodies is a crucial issue. In this paper we propose a new melodic similarity measure based on the I/R model for melodic structure and compare it with other existing measures. The experimentation shows that the proposed measure provides a good compromise between discriminatory power and ability to recognize phrases from the same song.\n
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\n \n\n \n \n \n \n \n Musical style recognition - a quantitative approach.\n \n \n \n\n\n \n Kranenburg, P. V.; and Backer, E.\n\n\n \n\n\n\n In Proceedings of the Conference on Interdisciplinary Musicology, pages 1–10, 2004. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    kranenburg.ea2004-musical,\n    author       = {Kranenburg, Peter Van and Backer, Eric},\n    year         = {2004},\n    title        = {Musical style recognition - a quantitative approach},\n    booktitle    = {Proceedings of the Conference on Interdisciplinary\n                   Musicology},\n    keywords     = {musicology},\n    mendeley-tags= {musicology},\n    pages        = {1--10}\n}\n\n
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\n \n\n \n \n \n \n \n Musical Proportion and Formal Function in Classical Sonata Form: Three Case Studies from Late Haydn and Early Beethoven.\n \n \n \n\n\n \n Mackay, J. S.\n\n\n \n\n\n\n Theory and Practice, 29(2004): 39–67. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          mackay2004-musical,\n    author       = {Mackay, James S.},\n    year         = {2004},\n    title        = {Musical Proportion and Formal Function in Classical\n                   Sonata Form: Three Case Studies from Late Haydn and Early\n                   Beethoven},\n    journal      = {Theory and Practice},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {2004},\n    pages        = {39--67},\n    volume       = {29}\n}\n\n
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\n  \n 2003\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Recapitulation Recomposition in the Sonata-Form First Movements of Haydn ' s String Quartets : Style Change and Compositional Technique.\n \n \n \n\n\n \n Larson, S.\n\n\n \n\n\n\n Music Analysis, 22(1/2): 139–177. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          larson2003-recapitulation,\n    author       = {Larson, Steve},\n    year         = {2003},\n    title        = {Recapitulation Recomposition in the Sonata-Form First\n                   Movements of Haydn ' s String Quartets : Style Change and\n                   Compositional Technique},\n    journal      = {Music Analysis},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1/2},\n    pages        = {139--177},\n    volume       = {22}\n}\n\n
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\n \n\n \n \n \n \n \n The Cambridge Companion to the String Q.\n \n \n \n\n\n \n Stowell, R.,\n editor.\n \n\n\n \n\n\n\n Cambridge University Press, Cambridge, UK, 2003.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             stowell2003-cambridge,\n    year         = {2003},\n    title        = {The Cambridge Companion to the String Q},\n    address      = {Cambridge, UK},\n    doi          = {10.1192/bjp.112.483.211-a},\n    editor       = {Stowell, Robin},\n    issn         = {0007-1250},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Cambridge University Press}\n}\n\n
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\n \n\n \n \n \n \n \n Uniformity, Balance, and Smoothness in Atonal Voice Leading.\n \n \n \n\n\n \n Straus, J. N.\n\n\n \n\n\n\n Music Theory Spectrum, 25(2): 305–352. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          straus2003-uniformity,\n    author       = {Straus, Joseph Nathan},\n    year         = {2003},\n    title        = {Uniformity, Balance, and Smoothness in Atonal Voice\n                   Leading},\n    abstract     = {[Unedited] Presents a broadly applicable model for atonal\n                   voice leading, a model of pitch-class counterpoint to\n                   connect any two harmonies. Voice leadings are evaluated by\n                   three criteria: (1) uniformity, the extent to which the\n                   voices move by the same interval distance and thus\n                   approach traditional transposition; (2) balance, the\n                   extent to which the voices move by the same index number\n                   and thus approach traditional inversion; and (3)\n                   smoothness, the extent to which the voices travel the\n                   shortest possible distance. The most uniform, most\n                   balanced, or smoothest way of moving from one set to\n                   another in pitch-class space, or from one set class to\n                   another in a proposed voice-leading space, provides a\n                   standpoint from which to assess any specific compositional\n                   realization in pitch space.},\n    doi          = {10.1525/mts.2003.25.2.305},\n    isbn         = {0195-6167},\n    issn         = {0195-6167},\n    journal      = {Music Theory Spectrum},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {2},\n    pages        = {305--352},\n    volume       = {25}\n}\n\n
\n
\n\n\n
\n [Unedited] Presents a broadly applicable model for atonal voice leading, a model of pitch-class counterpoint to connect any two harmonies. Voice leadings are evaluated by three criteria: (1) uniformity, the extent to which the voices move by the same interval distance and thus approach traditional transposition; (2) balance, the extent to which the voices move by the same index number and thus approach traditional inversion; and (3) smoothness, the extent to which the voices travel the shortest possible distance. The most uniform, most balanced, or smoothest way of moving from one set to another in pitch-class space, or from one set class to another in a proposed voice-leading space, provides a standpoint from which to assess any specific compositional realization in pitch space.\n
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\n  \n 2002\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Theories of musical rhythm in the eighteenth and nineteenth centuries.\n \n \n \n\n\n \n Caplin, W. E.\n\n\n \n\n\n\n In The Cambridge History of Western Music Theory, 21, pages 657–694. Cambridge University Press, Cambridge, UK, 2002.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@InCollection{     caplin2002-theories,\n    author       = {Caplin, William Earl},\n    year         = {2002},\n    title        = {Theories of musical rhythm in the eighteenth and\n                   nineteenth centuries},\n    abstract     = {Everyone agrees: it is di√cult to talk about rhythm in\n                   music, or, for that matter, the temporal experience in\n                   general. Compared with spatial relations, which appear to\n                   us as fixed and graspable, temporal ones seem fleeting and\n                   intangible. As a result, the lan-guage of time and rhythm\n                   is complex, contentious, and highly metaphorical.\n                   Considering that theorists today continue to have\n                   di√culty dealing with the metrical and durational\n                   organization of music from the eighteenth and nineteenth\n                   centuries – our most familiar music – it should come\n                   as no surprise that theoretical writings from those\n                   centuries often present themselves as perplexing and in\n                   need of explication. Though their manner of formulation\n                   may at times seem odd or convoluted, these theo-rists\n                   nonetheless ask many of the same questions about musical\n                   rhythm that underlie current concerns: What is a metrical\n                   accent? How do the profusion of time signatures relate to\n                   each other? Do the groupings of measures create a sense of\n                   larger-scale rhythm? Can various durational patterns be\n                   organized according to some scheme or another? How does\n                   our understanding of musical rhythm a◊ect performance,\n                   espe-cially tempo, phrasing, and articulation? Like many\n                   other domains of music theory, rhythmic theories are\n                   largely formulated in relation to a distinct compositional\n                   practice. Thus when compositional styles change, theorists\n                   respond by modifying their conceptions and formulating new\n                   ones in order better to reflect such transformations in\n                   practice. The high Baroque style, with its motoric pulses,\n                   regularized accentuations, and dance-derived rhythms,\n                   induced early eighteenth-century theorists to focus in\n                   detail on the classification of various metrical and\n                   durational patterns and to begin accounting for that most\n                   elusive concept – metrical accent. Later in the century,\n                   the emergence of the galant and Classical styles, with\n                   their emphasis on formal articulations, melodic\n                   prominence, and balanced phras-ings, stimulated theorists\n                   to consider the rhythms projected by phrase groupings and\n                   cadential goals. And some nineteenth-century Romantic\n                   idioms, whose phrase rhythms are even more regularized and\n                   symmetrical, encouraged theorists to promote varying (and\n                   often competing) schemes of hypermetrical organization.\n                   Though changes in musical style certainly prompted\n                   theoretical refinement and innovation, a strong conceptual\n                   inertia is evident in these writings. Thus early\n                   eigh-teenth-century rhythmic theory continued to be highly\n                   influenced by elements of the Renaissance mensural system,\n                   and it was not until much later in that century that an\n                   657 Cambridge Histories Online {\\textcopyright} Cambridge\n                   University Press, 2008 entirely modern conception of\n                   musical meter found systematic expression. This notion of\n                   meter then functioned as the basis for most\n                   nineteenth-century approaches. So, despite significant\n                   changes in compositional style, the sense of a " common\n                   prac-tice " of rhythmic organization is reflected through\n                   strong conceptual continuities in the theoretical thought\n                   of both centuries. Eighteenth-century theories:\n                   transition, innovation},\n    address      = {Cambridge, UK},\n    booktitle    = {The Cambridge History of Western Music Theory},\n    chapter      = {21},\n    doi          = {10.1017/chol9780521623711.023},\n    keywords     = {music history,music theory},\n    mendeley-tags= {music history,music theory},\n    pages        = {657--694},\n    publisher    = {Cambridge University Press}\n}\n\n
\n
\n\n\n
\n Everyone agrees: it is di√cult to talk about rhythm in music, or, for that matter, the temporal experience in general. Compared with spatial relations, which appear to us as fixed and graspable, temporal ones seem fleeting and intangible. As a result, the lan-guage of time and rhythm is complex, contentious, and highly metaphorical. Considering that theorists today continue to have di√culty dealing with the metrical and durational organization of music from the eighteenth and nineteenth centuries – our most familiar music – it should come as no surprise that theoretical writings from those centuries often present themselves as perplexing and in need of explication. Though their manner of formulation may at times seem odd or convoluted, these theo-rists nonetheless ask many of the same questions about musical rhythm that underlie current concerns: What is a metrical accent? How do the profusion of time signatures relate to each other? Do the groupings of measures create a sense of larger-scale rhythm? Can various durational patterns be organized according to some scheme or another? How does our understanding of musical rhythm a◊ect performance, espe-cially tempo, phrasing, and articulation? Like many other domains of music theory, rhythmic theories are largely formulated in relation to a distinct compositional practice. Thus when compositional styles change, theorists respond by modifying their conceptions and formulating new ones in order better to reflect such transformations in practice. The high Baroque style, with its motoric pulses, regularized accentuations, and dance-derived rhythms, induced early eighteenth-century theorists to focus in detail on the classification of various metrical and durational patterns and to begin accounting for that most elusive concept – metrical accent. Later in the century, the emergence of the galant and Classical styles, with their emphasis on formal articulations, melodic prominence, and balanced phras-ings, stimulated theorists to consider the rhythms projected by phrase groupings and cadential goals. And some nineteenth-century Romantic idioms, whose phrase rhythms are even more regularized and symmetrical, encouraged theorists to promote varying (and often competing) schemes of hypermetrical organization. Though changes in musical style certainly prompted theoretical refinement and innovation, a strong conceptual inertia is evident in these writings. Thus early eigh-teenth-century rhythmic theory continued to be highly influenced by elements of the Renaissance mensural system, and it was not until much later in that century that an 657 Cambridge Histories Online © Cambridge University Press, 2008 entirely modern conception of musical meter found systematic expression. This notion of meter then functioned as the basis for most nineteenth-century approaches. So, despite significant changes in compositional style, the sense of a \" common prac-tice \" of rhythmic organization is reflected through strong conceptual continuities in the theoretical thought of both centuries. Eighteenth-century theories: transition, innovation\n
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\n \n\n \n \n \n \n \n Como elaborar projetos de pesquisa.\n \n \n \n\n\n \n Gil, A. C.\n\n\n \n\n\n\n Atlas, São Paulo, 2002.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             gil2002-como,\n    author       = {Gil, Ant{\\^{o}}nio Carlos},\n    year         = {2002},\n    title        = {Como elaborar projetos de pesquisa},\n    address      = {S{\\~{a}}o Paulo},\n    isbn         = {8522431698},\n    keywords     = {research},\n    mendeley-tags= {research},\n    publisher    = {Atlas}\n}\n\n
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\n  \n 2001\n \n \n (7)\n \n \n
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\n \n\n \n \n \n \n \n Vienna.\n \n \n \n\n\n \n Antonicek, T.; Beales, D.; Botstein, L.; Klein, R.; and Goertz, H.\n\n\n \n\n\n\n 2001.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Misc{             antonicek.ea2001-vienna,\n    author       = {Antonicek, Theophil and Beales, Derek and Botstein, Leon\n                   and Klein, Rudolf and Goertz, Harald},\n    year         = {2001},\n    title        = {Vienna},\n    booktitle    = {Grove Music Online},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Oxford University Press}\n}\n\n
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\n \n\n \n \n \n \n \n \n Mozart.\n \n \n \n \n\n\n \n Eisen, C.; Rieger, E.; Eisen, C.; Sadie, S.; Angermüller, R.; Oldman, C B; and Stafford, W.\n\n\n \n\n\n\n 2001.\n \n\n\n\n
\n\n\n\n \n \n \"MozartPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Misc{             eisen.ea2001-mozart,\n    author       = {Eisen, Cliff and Rieger, Eva and Eisen, Cliff and Sadie,\n                   Stanley and Angerm{\\"{u}}ller, Rudolph and Oldman, C B and\n                   Stafford, William},\n    year         = {2001},\n    title        = {Mozart},\n    booktitle    = {Grove Music Online},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1},\n    publisher    = {Oxford University Press},\n    url          = {https://doi.org/10.1093/gmo/9781561592630.article.40258}\n}\n\n
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\n \n\n \n \n \n \n \n \n Concerto Style in Haydn's String Quartets.\n \n \n \n \n\n\n \n Grave, F. K.\n\n\n \n\n\n\n The Journal of Musicology, 18(1): 76–97. 2001.\n \n\n\n\n
\n\n\n\n \n \n \"ConcertoPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          grave2001-concerto,\n    author       = {Grave, Floyd K.},\n    year         = {2001},\n    title        = {Concerto Style in Haydn's String Quartets},\n    journal      = {The Journal of Musicology},\n    keywords     = {musicology},\n    mendeley-tags= {musicology},\n    number       = {1},\n    pages        = {76--97},\n    url          = {https://www.jstor.org/stable/10.1525/jm.2001.18.1.76},\n    volume       = {18}\n}\n\n
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\n \n\n \n \n \n \n \n \n The Haydn-Dedication Quartets: Allusion or Influence?.\n \n \n \n \n\n\n \n La Rue, J.\n\n\n \n\n\n\n Journal of Musicology, 18(2): 361–373. apr 2001.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          la-rue2001-haydn-dedication,\n    author       = {{La Rue}, Jan},\n    year         = {2001},\n    title        = {The Haydn-Dedication Quartets: Allusion or Influence?},\n    abstract     = {ETHICAL DECISION-MAKING ABOUT TRAUMA-RELATED STUDIES\n                   requires a flexible approach that counters assumptions and\n                   biases about victims, assures a favorable ethical\n                   cost-benefit ratio, and pro- motes advancement of\n                   knowledge that can benefit sur- vivors of traumatic\n                   stress. This paper reviews several ethical issues in the\n                   field of traumatic stress: benefit and risks in\n                   trauma-related research, whether trauma-related research\n                   poses unique risks and if so what those might be, informed\n                   consent and mandatory reporting, and supervision of\n                   trauma-related research. For each topic, we review\n                   potential ethical issues, summarize the research conducted\n                   thus far to inform ethical practice, and recommend future\n                   practice, research questions and policies to advance the\n                   field so that research on trauma can continue to be a\n                   win-win situation for all stakeholders in the research\n                   enterprise.},\n    doi          = {10.1525/jm.2001.18.2.361},\n    issn         = {0277-9269},\n    journal      = {Journal of Musicology},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    month        = {apr},\n    number       = {2},\n    pages        = {361--373},\n    url          = {http://jm.ucpress.edu/cgi/doi/10.1525/jm.2001.18.2.361},\n    volume       = {18}\n}\n\n
\n
\n\n\n
\n ETHICAL DECISION-MAKING ABOUT TRAUMA-RELATED STUDIES requires a flexible approach that counters assumptions and biases about victims, assures a favorable ethical cost-benefit ratio, and pro- motes advancement of knowledge that can benefit sur- vivors of traumatic stress. This paper reviews several ethical issues in the field of traumatic stress: benefit and risks in trauma-related research, whether trauma-related research poses unique risks and if so what those might be, informed consent and mandatory reporting, and supervision of trauma-related research. For each topic, we review potential ethical issues, summarize the research conducted thus far to inform ethical practice, and recommend future practice, research questions and policies to advance the field so that research on trauma can continue to be a win-win situation for all stakeholders in the research enterprise.\n
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\n \n\n \n \n \n \n \n \n Computers and music.\n \n \n \n \n\n\n \n Manning, P.; Selfridge-Field, E.; Reily, S. A.; and Pople, A.\n\n\n \n\n\n\n 2001.\n \n\n\n\n
\n\n\n\n \n \n \"ComputersPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Misc{             manning.ea2001-computers,\n    author       = {Manning, Peter and Selfridge-Field, Eleanor and Reily,\n                   Suzel Ana and Pople, Anthony},\n    year         = {2001},\n    title        = {Computers and music},\n    booktitle    = {Grove Music Online},\n    doi          = {10.1093/gmo/9781561592630.article.40583},\n    isbn         = {9781561592630},\n    keywords     = {computer and music},\n    mendeley-tags= {computer and music},\n    pages        = {1--37},\n    publisher    = {Oxford University Press},\n    url          = {http://www.oxfordmusiconline.com/grovemusic/view/10.1093/gmo/9781561592630.001.0001/omo-9781561592630-e-0000040583},\n    volume       = {1}\n}\n\n
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\n \n\n \n \n \n \n \n Música na Escola Brasileira. Frequência de elementos musicais em canções vernáculas da Bahia utilizando análise manual e por computador: sugestões para aplicação na Educação Musical.\n \n \n \n\n\n \n Oliveira, A. d. J.\n\n\n \n\n\n\n Teses na Educação Musical, (2). 2001.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          oliveira2001-musica,\n    author       = {Oliveira, Alda de Jesus},\n    year         = {2001},\n    title        = {M{\\'{u}}sica na Escola Brasileira. Frequ{\\^{e}}ncia de\n                   elementos musicais em can{\\c{c}}{\\~{o}}es vern{\\'{a}}culas\n                   da Bahia utilizando an{\\'{a}}lise manual e por computador:\n                   sugest{\\~{o}}es para aplica{\\c{c}}{\\~{a}}o na\n                   Educa{\\c{c}}{\\~{a}}o Musical},\n    address      = {Porto Alegre},\n    journal      = {Teses na Educa{\\c{c}}{\\~{a}}o Musical},\n    keywords     = {music education},\n    mendeley-tags= {music education},\n    number       = {2},\n    publisher    = {Associa{\\c{c}}{\\~{a}}o Brasileira de Educa{\\c{c}}{\\~{a}}o\n                   Musical}\n}\n\n
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\n \n\n \n \n \n \n \n \n Haydn, (Franz) Joseph.\n \n \n \n \n\n\n \n Webster, J.; and Feder, G.\n\n\n \n\n\n\n 2001.\n \n\n\n\n
\n\n\n\n \n \n \"Haydn,Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Misc{             webster.ea2001-haydn,\n    author       = {Webster, James and Feder, Georg},\n    year         = {2001},\n    title        = {Haydn, (Franz) Joseph},\n    booktitle    = {Grove Music Online},\n    doi          = {10.1093/gmo/9781561592630.article.44593},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Oxford University Press},\n    url          = {http://www.oxfordmusiconline.com/grovemusic/view/10.1093/gmo/9781561592630.001.0001/omo-9781561592630-e-0000044593}\n}\n\n
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\n  \n 2000\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n A reader's guide to Haydn's early string quartets.\n \n \n \n\n\n \n Drabkin, W.\n\n\n \n\n\n\n Greenwood Press, Wesport, CT, 2000.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             drabkin2000-readers,\n    author       = {Drabkin, William},\n    year         = {2000},\n    title        = {A reader's guide to Haydn's early string quartets},\n    address      = {Wesport, CT},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    publisher    = {Greenwood Press}\n}\n\n
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\n \n\n \n \n \n \n \n \n String quartet.\n \n \n \n \n\n\n \n Eisen, C.; Baldassare, A.; and Griffiths, P.\n\n\n \n\n\n\n 2000.\n \n\n\n\n
\n\n\n\n \n \n \"StringPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Misc{             eisen.ea2000-string,\n    author       = {Eisen, Cliff and Baldassare, Antonio and Griffiths,\n                   Paul},\n    year         = {2000},\n    title        = {String quartet},\n    booktitle    = {Grove Music Online},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Oxford University Press},\n    url          = {http://www.oxfordmusiconline.com/subscriber/article/grove/music/40899}\n}\n\n
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\n \n\n \n \n \n \n \n String Quartets Op 17, Complete.\n \n \n \n\n\n \n Haydn, J.\n\n\n \n\n\n\n Dover Publications, Inc, Mineola, NY, 2000.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             haydn2000-string,\n    author       = {Haydn, Joseph},\n    year         = {2000},\n    title        = {String Quartets Op 17, Complete},\n    address      = {Mineola, NY},\n    editor       = {Altmann, Wilhelm},\n    keywords     = {music score},\n    mendeley-tags= {music score},\n    publisher    = {Dover Publications, Inc}\n}\n\n
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\n \n\n \n \n \n \n \n \n Beethoven, Ludwig van.\n \n \n \n \n\n\n \n Kerman, J.; Tyson, A.; Burnham, S. G.; Douglas Johnson; and Drabkin, W.\n\n\n \n\n\n\n 2000.\n \n\n\n\n
\n\n\n\n \n \n \"Beethoven,Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Misc{             kerman.ea2000-beethoven,\n    author       = {Kerman, Joseph and Tyson, Alan and Burnham, Scott G. and\n                   {Douglas Johnson} and Drabkin, William},\n    year         = {2000},\n    title        = {Beethoven, Ludwig van},\n    booktitle    = {Grove Music Online},\n    doi          = {10.1093/gmo/9781561592630.article.40026},\n    isbn         = {9781561592630},\n    keywords     = {musicology},\n    mendeley-tags= {musicology},\n    publisher    = {Oxford University Press},\n    url          = {http://www.oxfordmusiconline.com/subscriber/article/grove/music/40026}\n}\n\n
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\n \n\n \n \n \n \n \n Techniques of expression in Viennese string music (1780-1830) : reconstructing fingering and bowing practices.\n \n \n \n\n\n \n Moran, J. G.\n\n\n \n\n\n\n Ph.D. Thesis, University of London, 2000.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        moran2000-techniques,\n    author       = {Moran, John Gregory},\n    year         = {2000},\n    title        = {Techniques of expression in Viennese string music\n                   (1780-1830) : reconstructing fingering and bowing\n                   practices},\n    abstract     = {Though Viennese classical music for strings is central to\n                   the standard repertory and is steadily attracting more\n                   performances by 'historically informed' players, awareness\n                   of the practices of the Viennese players amongst whom\n                   Haydn and Beethoven worked remains limited. Studies of the\n                   string playing practices ostensibly appropriate to\n                   Beethoven have generally been based on instrumental\n                   treatises representative of other traditions, either later\n                   in time or geographically remote. This thesis attempts to\n                   reconstruct the unique traits of the fingering and bowing\n                   practices surrounding Haydn and Beethoven in Vienna\n                   through the surviving evidence most closely connected with\n                   them and the players for whom they composed. The sources\n                   include Haydn's and Beethoven's string fingerings and\n                   slurs; the music of players with whom these composers were\n                   associated, including Krumpholz, Wranitzky, Schuppanzigh,\n                   Mayseder, the Krafts, and Linke; and the rarely considered\n                   technical studies and string treatises of Vienna,\n                   including those by Kauer, Pith!, Pirlinger, and Schweigl.\n                   This thesis begins with a survey of the string players in\n                   the circles of Haydn, Mozart, Schubert, and especially\n                   Beethoven, discussing their significance and playing\n                   styles, contrasting Viennese practices with the more\n                   progressive approaches of Paris. The diversity of Viennese\n                   fingering practices forms the basis for the second\n                   chapter's examination of the wealth of information which\n                   can be conveyed by apparently simple fingerings. Haydn's\n                   and Beethoven's original fingerings, together accounting\n                   for approximately three hundred passages, are the subjects\n                   of chapters three and four. The fifth chapter considers\n                   tone production and the myth of the 'phrasing' slur in\n                   string writing, while the sixth is an investigation of\n                   what constituted the basic repertory of bow strokes. The\n                   final chapter, a case study of a set of marked parts to\n                   Beethoven's op. 59, no. 3 quartet, shows how the various\n                   methods of reconstruction developed in this thesis can be\n                   brought together in the context of a complete work.},\n    keywords     = {music performance},\n    mendeley-tags= {music performance},\n    school       = {University of London},\n    type         = {Ph.D. Thesis}\n}\n\n
\n
\n\n\n
\n Though Viennese classical music for strings is central to the standard repertory and is steadily attracting more performances by 'historically informed' players, awareness of the practices of the Viennese players amongst whom Haydn and Beethoven worked remains limited. Studies of the string playing practices ostensibly appropriate to Beethoven have generally been based on instrumental treatises representative of other traditions, either later in time or geographically remote. This thesis attempts to reconstruct the unique traits of the fingering and bowing practices surrounding Haydn and Beethoven in Vienna through the surviving evidence most closely connected with them and the players for whom they composed. The sources include Haydn's and Beethoven's string fingerings and slurs; the music of players with whom these composers were associated, including Krumpholz, Wranitzky, Schuppanzigh, Mayseder, the Krafts, and Linke; and the rarely considered technical studies and string treatises of Vienna, including those by Kauer, Pith!, Pirlinger, and Schweigl. This thesis begins with a survey of the string players in the circles of Haydn, Mozart, Schubert, and especially Beethoven, discussing their significance and playing styles, contrasting Viennese practices with the more progressive approaches of Paris. The diversity of Viennese fingering practices forms the basis for the second chapter's examination of the wealth of information which can be conveyed by apparently simple fingerings. Haydn's and Beethoven's original fingerings, together accounting for approximately three hundred passages, are the subjects of chapters three and four. The fifth chapter considers tone production and the myth of the 'phrasing' slur in string writing, while the sixth is an investigation of what constituted the basic repertory of bow strokes. The final chapter, a case study of a set of marked parts to Beethoven's op. 59, no. 3 quartet, shows how the various methods of reconstruction developed in this thesis can be brought together in the context of a complete work.\n
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\n  \n 1999\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n Music Research Using Humdrum: A User's Guide.\n \n \n \n\n\n \n Huron, D.\n\n\n \n\n\n\n 1999.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Misc{             huron1999-music,\n    author       = {Huron, David},\n    year         = {1999},\n    title        = {Music Research Using Humdrum: A User's Guide},\n    address      = {Stanford, CA},\n    publisher    = {Center for Computer Assisted Research in the Humanities}\n}\n\n
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\n \n\n \n \n \n \n \n \n The New Empiricism: Systematic Musicology in a Postmodern Age.\n \n \n \n \n\n\n \n Huron, D.\n\n\n \n\n\n\n 1999.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Misc{             huron1999-new,\n    author       = {Huron, David},\n    year         = {1999},\n    title        = {The New Empiricism: Systematic Musicology in a Postmodern\n                   Age},\n    abstract     = {A survey of intellectual currents in the philosophy of\n                   knowledge and research methodology is given. This survey\n                   provides the backdrop for taking stock of the\n                   methodological differences that have arisen between\n                   disciplines, such as the methods commonly used in science,\n                   history or literary theory. Postmodernism and scientific\n                   empiricism are described and portrayed as two sides of the\n                   same coin we call skepticism. It is proposed that the\n                   choice of methodological approach for any given research\n                   program is guided by moral and esthetic considerations.\n                   Careful assessment of these risks may suggest choosing an\n                   unorthodox method, such as quantitative methods in\n                   history, or deconstruction in science. It is argued that\n                   methodological tools (such as Ockham's razor) should not\n                   be mistaken for philosophical world-views. The article\n                   advocates a broadening of methodological education in both\n                   arts and sciences disciplines. In particular, it advocates\n                   and defends the use of quantitative empirical methodology\n                   in various areas of music scholarship.},\n    booktitle    = {Ernest Bloch Lectures},\n    keywords     = {computational musicology,evolution,lecture,music\n                   cognition,psychology,theory},\n    mendeley-tags= {computational musicology},\n    url          = {http://www.musiccog.ohio-state.edu/Music220/Bloch.lectures/2.Origins.html}\n}\n\n
\n
\n\n\n
\n A survey of intellectual currents in the philosophy of knowledge and research methodology is given. This survey provides the backdrop for taking stock of the methodological differences that have arisen between disciplines, such as the methods commonly used in science, history or literary theory. Postmodernism and scientific empiricism are described and portrayed as two sides of the same coin we call skepticism. It is proposed that the choice of methodological approach for any given research program is guided by moral and esthetic considerations. Careful assessment of these risks may suggest choosing an unorthodox method, such as quantitative methods in history, or deconstruction in science. It is argued that methodological tools (such as Ockham's razor) should not be mistaken for philosophical world-views. The article advocates a broadening of methodological education in both arts and sciences disciplines. In particular, it advocates and defends the use of quantitative empirical methodology in various areas of music scholarship.\n
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\n \n\n \n \n \n \n \n \n Texture, Register, and Their Formal Roles in the Music of Witold Lutosławski.\n \n \n \n \n\n\n \n Klein, M.\n\n\n \n\n\n\n Indiana Theory Review, 20: 37–70. 1999.\n \n\n\n\n
\n\n\n\n \n \n \"Texture,Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          klein1999-texture,\n    author       = {Klein, Michael},\n    year         = {1999},\n    title        = {Texture, Register, and Their Formal Roles in the Music of\n                   Witold Lutos{\\l}awski},\n    doi          = {10.2307/24044509},\n    journal      = {Indiana Theory Review},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    pages        = {37--70},\n    url          = {https://www.jstor.org/stable/24044509},\n    volume       = {20}\n}\n\n
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\n \n\n \n \n \n \n \n Testing Models of Melodic Contour Similarity.\n \n \n \n\n\n \n Schmuckler, M. A.\n\n\n \n\n\n\n Music Perception, 16(3): 295–326. 1999.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          schmuckler1999-testing,\n    author       = {Schmuckler, Mark A.},\n    year         = {1999},\n    title        = {Testing Models of Melodic Contour Similarity},\n    journal      = {Music Perception},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    number       = {3},\n    pages        = {295--326},\n    volume       = {16}\n}\n\n
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\n \n\n \n \n \n \n \n Continuous Exposition and Tonal Structure in Three Late Haydn Works.\n \n \n \n\n\n \n Suurpaa, L.\n\n\n \n\n\n\n Music Theory Spectrum, 21(2): 174–199. 1999.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          suurpaa1999-continuous,\n    author       = {Suurpaa, Lauri},\n    year         = {1999},\n    title        = {Continuous Exposition and Tonal Structure in Three Late\n                   Haydn Works},\n    doi          = {10.1525/mts.1999.21.2.02a00020},\n    issn         = {0195-6167},\n    journal      = {Music Theory Spectrum},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {2},\n    pages        = {174--199},\n    volume       = {21}\n}\n\n
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\n \n\n \n \n \n \n \n \n What's Key for Key? The Krumhansl-Schmuckler Key-Finding Algorithm Reconsidered.\n \n \n \n \n\n\n \n Temperley, D.\n\n\n \n\n\n\n Music Perception, 17(1): 65–100. oct 1999.\n \n\n\n\n
\n\n\n\n \n \n \"What'sPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Article{          temperley1999-whats,\n    author       = {Temperley, David},\n    year         = {1999},\n    title        = {What's Key for Key? The Krumhansl-Schmuckler Key-Finding\n                   Algorithm Reconsidered},\n    abstract     = {This study examines the Krumhansl-Schmuckler key-finding\n                   model, in which the distribution of pitch classes in a\n                   piece is compared with an ideal distribution or "key\n                   profile" for each key. Several changes are proposed.\n                   First, the formula used for the matching process is\n                   somewhat simplified. Second, alternative values are\n                   proposed for the key profiles themselves. Third, rather\n                   than summing the durations of all events of each pitch\n                   class, the revised model divides the piece into short\n                   segments and labels each pitch class as present or absent\n                   in each segment. Fourth, a mechanism for modulation is\n                   proposed; a penalty is imposed for changing key from one\n                   segment to the next. An implementation of this model was\n                   subjected to two tests. First, the model was tested on the\n                   fugue subjects from Bach's Well-Tempered Clavier; the\n                   model's performance on this corpus is compared with the\n                   performances of other models. Second, the model was tested\n                   on a corpus of excerpts from the Kostka and Payne harmony\n                   textbook (as analyzed by Kostka). Several problems with\n                   the modified algorithm are discussed, concerning the rate\n                   of modulation, the role of harmony in key finding, and the\n                   role of pitch "spellings." The model is also compared with\n                   Huron and Parncutt's exponential decay model. The tests\n                   presented here suggest that the key-profile model, with\n                   the modifications proposed, can provide a highly\n                   successful approach to key finding.},\n    doi          = {10.2307/40285812},\n    issn         = {0730-7829},\n    journal      = {Music Perception},\n    month        = {oct},\n    number       = {1},\n    pages        = {65--100},\n    url          = {https://online.ucpress.edu/mp/article/17/1/65/62051/Whats-Key-for-Key-The-KrumhanslSchmuckler},\n    volume       = {17}\n}\n\n
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\n This study examines the Krumhansl-Schmuckler key-finding model, in which the distribution of pitch classes in a piece is compared with an ideal distribution or \"key profile\" for each key. Several changes are proposed. First, the formula used for the matching process is somewhat simplified. Second, alternative values are proposed for the key profiles themselves. Third, rather than summing the durations of all events of each pitch class, the revised model divides the piece into short segments and labels each pitch class as present or absent in each segment. Fourth, a mechanism for modulation is proposed; a penalty is imposed for changing key from one segment to the next. An implementation of this model was subjected to two tests. First, the model was tested on the fugue subjects from Bach's Well-Tempered Clavier; the model's performance on this corpus is compared with the performances of other models. Second, the model was tested on a corpus of excerpts from the Kostka and Payne harmony textbook (as analyzed by Kostka). Several problems with the modified algorithm are discussed, concerning the rate of modulation, the role of harmony in key finding, and the role of pitch \"spellings.\" The model is also compared with Huron and Parncutt's exponential decay model. The tests presented here suggest that the key-profile model, with the modifications proposed, can provide a highly successful approach to key finding.\n
\n\n\n
\n\n\n\n\n\n
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\n\n
\n
\n  \n 1998\n \n \n (5)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Surprising Returns: The VII # in Beethoven's Op. 18 No. 3, and Its Antecedents in Haydn.\n \n \n \n \n\n\n \n Burstein, L. P.\n\n\n \n\n\n\n Music Analysis, 17(3): 295–312. 1998.\n \n\n\n\n
\n\n\n\n \n \n \"SurprisingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          burstein1998-surprising,\n    author       = {Burstein, L. Poundie},\n    year         = {1998},\n    title        = {Surprising Returns: The VII \\# in Beethoven's Op. 18 No.\n                   3, and Its Antecedents in Haydn},\n    isbn         = {9788578110796},\n    issn         = {1098-6596},\n    journal      = {Music Analysis},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {3},\n    pages        = {295--312},\n    url          = {http://www.jstor.org/stable/854418},\n    volume       = {17}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Classical Form: A Theory of Formal Functions for the Instrumental Music of Haydn, Mozart, and Beethoven.\n \n \n \n\n\n \n Caplin, W. E.\n\n\n \n\n\n\n Oxford University Press, New York, 1998.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             caplin1998-classical,\n    author       = {Caplin, William Earl},\n    year         = {1998},\n    title        = {Classical Form: A Theory of Formal Functions for the\n                   Instrumental Music of Haydn, Mozart, and Beethoven},\n    address      = {New York},\n    booktitle    = {Nordamerikanische Musiktheorie},\n    isbn         = {0195104803},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {Oxford University Press}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Voice-leading spaces.\n \n \n \n \n\n\n \n Morris, R. D.\n\n\n \n\n\n\n Music Theory Spectrum, 20(2): 175–208. 1998.\n \n\n\n\n
\n\n\n\n \n \n \"Voice-leadingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          morris1998-voice-leading,\n    author       = {Morris, Robert Daniel},\n    year         = {1998},\n    title        = {Voice-leading spaces},\n    issn         = {0195-6167},\n    journal      = {Music Theory Spectrum},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {2},\n    pages        = {175--208},\n    publisher    = {JSTOR},\n    url          = {http://www.jstor.org/stable/746047},\n    volume       = {20}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Haydn Studies.\n \n \n \n\n\n \n Sutcliffe, W. D.,\n editor.\n \n\n\n \n\n\n\n Cambridge University Press, Cambridge, 1998.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@Book{             sutcliffe1998-haydn,\n    year         = {1998},\n    title        = {Haydn Studies},\n    address      = {Cambridge},\n    editor       = {Sutcliffe, W. Dean},\n    isbn         = {9780521028356},\n    keywords     = {haydn,music history},\n    mendeley-tags= {haydn,music history},\n    publisher    = {Cambridge University Press}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n CRC Concise Encyclopedia of Mathematics.\n \n \n \n \n\n\n \n Weisstein, E. W.\n\n\n \n\n\n\n CRC Press, Boca Raton, FL, 1998.\n \n\n\n\n
\n\n\n\n \n \n \"CRCPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@Book{             weisstein1998-crc,\n    author       = {Weisstein, Eric W.},\n    year         = {1998},\n    title        = {CRC Concise Encyclopedia of Mathematics},\n    address      = {Boca Raton, FL},\n    keywords     = {Mathematics--Encyclopedias,mathematics},\n    mendeley-tags= {mathematics},\n    pages        = {1973},\n    publisher    = {CRC Press},\n    url          = {http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:CRC+Concise+Encyclopedia+of+Mathematics#0}\n}\n\n
\n
\n\n\n\n
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\n\n
\n
\n  \n 1997\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n A bibliography of statistical applications in musicology.\n \n \n \n\n\n \n Nettheim, N.\n\n\n \n\n\n\n Musicology Australia, 20(1): 94–106. 1997.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          nettheim1997-bibliography,\n    author       = {Nettheim, Nigel},\n    year         = {1997},\n    title        = {A bibliography of statistical applications in\n                   musicology},\n    abstract     = {Statistical applications in musicology appear in widely\n                   scattered publications. The present bibliography, mainly\n                   of English language publications, extends back to the\n                   beginning of the present century. The analysis of musical\n                   scores is emphasized, but applications in the social\n                   sciences arc also touched upon, as well as those to\n                   performance studies and algorithmic composition.\n                   Statistical techniques include simple summarization,\n                   graphical methods, time series analysis, information\n                   theory, Zipf's law, Markov chains, fractals, and neural\n                   networks. Several cases of misapplication of statistics\n                   are noted. Commentary is provided on the field and its\n                   sub-fields. {\\textcopyright} 1997, Taylor \\& Francis\n                   Group, LLC. All rights reserved.},\n    doi          = {10.1080/08145857.1997.10415974},\n    issn         = {1949453X},\n    journal      = {Musicology Australia},\n    keywords     = {music and mathematics},\n    mendeley-tags= {music and mathematics},\n    number       = {1},\n    pages        = {94--106},\n    volume       = {20}\n}\n\n
\n
\n\n\n
\n Statistical applications in musicology appear in widely scattered publications. The present bibliography, mainly of English language publications, extends back to the beginning of the present century. The analysis of musical scores is emphasized, but applications in the social sciences arc also touched upon, as well as those to performance studies and algorithmic composition. Statistical techniques include simple summarization, graphical methods, time series analysis, information theory, Zipf's law, Markov chains, fractals, and neural networks. Several cases of misapplication of statistics are noted. Commentary is provided on the field and its sub-fields. © 1997, Taylor & Francis Group, LLC. All rights reserved.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n The Classical Style: Haydn, Mozart, Beethoven.\n \n \n \n \n\n\n \n Rosen, C.\n\n\n \n\n\n\n W. W. Norton & Company, New York, NY, Expanded e edition, 1997.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             rosen1997-classical,\n    author       = {Rosen, Charles},\n    year         = {1997},\n    title        = {The Classical Style: Haydn, Mozart, Beethoven},\n    address      = {New York, NY},\n    edition      = {Expanded e},\n    isbn         = {0393040208},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {W. W. Norton \\& Company},\n    url          = {https://pt.scribd.com/doc/124143289/Charles-Rosen-The-Classical-Style-Haydn-Mozart-Beethoven}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Haydn and his World.\n \n \n \n\n\n \n Sisman, E.\n\n\n \n\n\n\n Princeton University Press, Princeton, NJ, 1997.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             sisman1997-haydn,\n    author       = {Sisman, Elaine},\n    year         = {1997},\n    title        = {Haydn and his World},\n    address      = {Princeton, NJ},\n    isbn         = {0691057982},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Princeton University Press}\n}\n\n
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\n
\n  \n 1996\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n The Critical Editing of Music: History, Method, and Practice.\n \n \n \n\n\n \n Grier, J.\n\n\n \n\n\n\n Cambridge University Press, New York, NY, 1996.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             grier1996-critical,\n    author       = {Grier, James},\n    year         = {1996},\n    title        = {The Critical Editing of Music: History, Method, and\n                   Practice},\n    address      = {New York, NY},\n    keywords     = {musicology},\n    mendeley-tags= {musicology},\n    publisher    = {Cambridge University Press}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n What is melodic accent? Converging evidence from musical practice.\n \n \n \n \n\n\n \n Huron, D.; and Royal, M.\n\n\n \n\n\n\n Music Perception, 13(4): 489–516. 1996.\n \n\n\n\n
\n\n\n\n \n \n \"WhatPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          huron.ea1996-what,\n    author       = {Huron, David and Royal, Mathew},\n    year         = {1996},\n    title        = {What is melodic accent? Converging evidence from musical\n                   practice},\n    issn         = {0730-7829},\n    journal      = {Music Perception},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {4},\n    pages        = {489--516},\n    publisher    = {JSTOR},\n    url          = {http://www.jstor.org/stable/40285700},\n    volume       = {13}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n The Melodic Arch in Western Folksongs.\n \n \n \n \n\n\n \n Huron, D.\n\n\n \n\n\n\n Computing in Musicology, 10: 3–23. 1996.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          huron1996-melodic,\n    author       = {Huron, David},\n    year         = {1996},\n    title        = {The Melodic Arch in Western Folksongs},\n    issn         = {1057-9478},\n    journal      = {Computing in Musicology},\n    pages        = {3--23},\n    url          = {https://csml.som.ohio-state.edu/Huron/Publications/huron.arch.text.html},\n    volume       = {10}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A Generative Theory of Tonal Music.\n \n \n \n\n\n \n Lerdahl, F.; and Jackendoff, R. S.\n\n\n \n\n\n\n MIT Press, 1996.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             lerdahl.ea1996-generative,\n    author       = {Lerdahl, Fred and Jackendoff, Ray S.},\n    year         = {1996},\n    title        = {A Generative Theory of Tonal Music},\n    isbn         = {9780262621076},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {MIT Press}\n}\n\n
\n
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\n  \n 1995\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Metrical Dissonance in Haydn.\n \n \n \n \n\n\n \n Grave, F. K.\n\n\n \n\n\n\n The Journal of Musicology, 13(2): 168–202. 1995.\n \n\n\n\n
\n\n\n\n \n \n \"MetricalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          grave1995-metrical,\n    author       = {Grave, Floyd K.},\n    year         = {1995},\n    title        = {Metrical Dissonance in Haydn},\n    journal      = {The Journal of Musicology},\n    keywords     = {musicology},\n    mendeley-tags= {musicology},\n    number       = {2},\n    pages        = {168--202},\n    url          = {https://www.jstor.org/stable/764104?Search=yes&resultItemClick=true&searchText=au%3A&searchText=%22grave%22&searchUri=%2Faction%2FdoBasicSearch%3FQuery%3Dau%253A%2522grave%2522&ab_segments=0%2Fbasic_SYC-4341%2Ftest&refreqid=search%3Adea0fe7557373c9b7c9f88},\n    volume       = {13}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n The Humdrum Toolkit: Reference Manual.\n \n \n \n\n\n \n Huron, D.\n\n\n \n\n\n\n 1995.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Misc{             huron1995-humdrum,\n    author       = {Huron, David},\n    year         = {1995},\n    title        = {The Humdrum Toolkit: Reference Manual},\n    address      = {Menlo Park, CA},\n    publisher    = {Center for Computer Assisted Research in the Humanities}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Tonal harmony, with an introduction to twentieth-century music.\n \n \n \n\n\n \n Kostka, S. M.; and Payne, D.\n\n\n \n\n\n\n McGraw-Hill, New York, NY, 3rd edition, 1995.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             kostka.ea1995-tonal,\n    author       = {Kostka, Stefan M. and Payne, Dorothy},\n    year         = {1995},\n    title        = {Tonal harmony, with an introduction to twentieth-century\n                   music},\n    address      = {New York, NY},\n    edition      = {3rd},\n    isbn         = {0072415703},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {McGraw-Hill}\n}\n\n
\n
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\n\n
\n
\n  \n 1994\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Music Reference and Research Materials: An Annotated Bibliography.\n \n \n \n\n\n \n Duckles, V. H; and Keller, M. A\n\n\n \n\n\n\n Schirmer Books, New York, 4th edition, 1994.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             duckles.ea1994-music,\n    author       = {Duckles, Vincent H and Keller, Michael A},\n    year         = {1994},\n    title        = {Music Reference and Research Materials: An Annotated\n                   Bibliography},\n    address      = {New York},\n    edition      = {4th},\n    keywords     = {music},\n    mendeley-tags= {music},\n    publisher    = {Schirmer Books}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n The Beethoven Quartet Companion.\n \n \n \n\n\n \n Winter, R.; and Martin, R.,\n editors.\n \n\n\n \n\n\n\n University of California Press, Berkeley, CA, 1994.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             winter.ea1994-beethoven,\n    year         = {1994},\n    title        = {The Beethoven Quartet Companion},\n    address      = {Berkeley, CA},\n    editor       = {Winter, Robert and Martin, Robert},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {University of California Press}\n}\n\n
\n
\n\n\n\n
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\n\n
\n
\n  \n 1993\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Computational Musicology A Survey on Methodologies and Applications.\n \n \n \n\n\n \n Camilleri, L.\n\n\n \n\n\n\n Revue Informatique et Statistique dans les Sciences humaines, XXIX: 51–65. 1993.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          camilleri1993-computational,\n    author       = {Camilleri, Lelio},\n    year         = {1993},\n    title        = {Computational Musicology A Survey on Methodologies and\n                   Applications},\n    abstract     = {Cet article traite de J'utilisation de l'i.nformatique\n                   dans les {\\'{e}}tudes de musique. Il pr{\\'{e}}sente une\n                   introduction aux diff{\\'{e}}rents aspects de la\n                   musicologie computationnelle el aux r{\\'{e}}cents\n                   d{\\'{e}}veloppe- ments dan!'> ce domaine. Il passe en\n                   revue les principales applications de l'informatique en\n                   musicologie historique ct en analyse quelques exemples et\n                   leurs implications. Ensuite sont d{\\'{e}}crites les\n                   applications de l'ordinateur aux {\\'{e}}ludes analytiques\n                   en cc qui concerne leurs aspects m{\\'{e}}thodologiques.\n                   Des exemples de syst{\\`{e}}mes d'analyse automatique sont\n                   expliqu{\\'{e}}s avec les conclusions th{\\'{e}}oriques que\n                   l'on peut cn tirer. L'article s'ach{\\`{e}}ve par une\n                   analyse rapide de d{\\'{e}}veloppements\n                   cn\\,jsageablc.$\\sim$ dans le futur.},\n    journal      = {Revue Informatique et Statistique dans les Sciences\n                   humaines},\n    keywords     = {computational musicology},\n    mendeley-tags= {computational musicology},\n    pages        = {51--65},\n    volume       = {XXIX}\n}\n\n
\n
\n\n\n
\n Cet article traite de J'utilisation de l'i.nformatique dans les études de musique. Il présente une introduction aux différents aspects de la musicologie computationnelle el aux récents développe- ments dan!'> ce domaine. Il passe en revue les principales applications de l'informatique en musicologie historique ct en analyse quelques exemples et leurs implications. Ensuite sont décrites les applications de l'ordinateur aux éludes analytiques en cc qui concerne leurs aspects méthodologiques. Des exemples de systèmes d'analyse automatique sont expliqués avec les conclusions théoriques que l'on peut cn tirer. L'article s'achève par une analyse rapide de développements cn\\,jsageablc.$∼$ dans le futur.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n New Directions in the Theory and Analysis of Musical Contour.\n \n \n \n \n\n\n \n Morris, R. D.\n\n\n \n\n\n\n Music Theory Spectrum, 15(2): 205–228. oct 1993.\n \n\n\n\n
\n\n\n\n \n \n \"NewPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          morris1993-new,\n    author       = {Morris, Robert Daniel},\n    year         = {1993},\n    title        = {New Directions in the Theory and Analysis of Musical\n                   Contour},\n    doi          = {10.1525/mts.1993.15.2.02a00040},\n    issn         = {0195-6167},\n    journal      = {Music Theory Spectrum},\n    month        = {oct},\n    number       = {2},\n    pages        = {205--228},\n    url          = {http://caliber.ucpress.net/doi/abs/10.1525/mts.1993.15.2.02a00040},\n    volume       = {15}\n}\n\n
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\n  \n 1992\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Beethoven: studies in the creative process.\n \n \n \n\n\n \n Lockwood, L.\n\n\n \n\n\n\n Harvard University Press, Cambridge, MA; London, 1992.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Book{             lockwood1992-beethoven,\n    author       = {Lockwood, Lewis},\n    year         = {1992},\n    title        = {Beethoven: studies in the creative process},\n    address      = {Cambridge, MA; London},\n    isbn         = {0674063627 (acid-free paper)},\n    publisher    = {Harvard University Press}\n}\n\n
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\n \n\n \n \n \n \n \n Haydn: String Quartets, Op. 50.\n \n \n \n\n\n \n Sutcliffe, W. D.\n\n\n \n\n\n\n Cambridge University Press, Cambridge, 1992.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             sutcliffe1992-haydn,\n    author       = {Sutcliffe, W. Dean},\n    year         = {1992},\n    title        = {Haydn: String Quartets, Op. 50},\n    address      = {Cambridge},\n    editor       = {Rushton, Julian},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Cambridge University Press}\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n Beethoven's \"Mozart\" Quartet.\n \n \n \n\n\n \n Yudkin, J.\n\n\n \n\n\n\n Journal of the American Musicological Society, 45(1): 30–74. 1992.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          yudkin1992-beethovens,\n    author       = {Yudkin, Jeremy},\n    year         = {1992},\n    title        = {Beethoven's "Mozart" Quartet},\n    journal      = {Journal of the American Musicological Society},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1},\n    pages        = {30--74},\n    volume       = {45}\n}\n
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\n  \n 1991\n \n \n (1)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n Engaging Strategies in Haydn's Opus 33 String Quartets.\n \n \n \n\n\n \n Wheelock, G. A.\n\n\n \n\n\n\n Eighteenth-Century Studies, 25(1): 1–30. 1991.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          wheelock1991-engaging,\n    author       = {Wheelock, Gretchen A.},\n    year         = {1991},\n    title        = {Engaging Strategies in Haydn's Opus 33 String Quartets},\n    journal      = {Eighteenth-Century Studies},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1},\n    pages        = {1--30},\n    volume       = {25}\n}\n\n
\n
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\n\n
\n
\n  \n 1989\n \n \n (2)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n A Teoria de Heinrich Schenker: uma breve introdução.\n \n \n \n\n\n \n Gerling, C. C.\n\n\n \n\n\n\n Em Pauta, 1(1): 22–34. 1989.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          gerling1989-teoria,\n    author       = {Gerling, Cristina Capparelli},\n    year         = {1989},\n    title        = {A Teoria de Heinrich Schenker: uma breve\n                   introdu{\\c{c}}{\\~{a}}o},\n    journal      = {Em Pauta},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {1},\n    pages        = {22--34},\n    volume       = {1}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition.\n \n \n \n\n\n \n Rabiner, L. R.\n\n\n \n\n\n\n In Proceedings of the IEEE, pages 257–286, 1989. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    rabiner1989-tutorial,\n    author       = {Rabiner, Lawrence R.},\n    year         = {1989},\n    title        = {A Tutorial on Hidden Markov Models and Selected\n                   Applications in Speech Recognition},\n    booktitle    = {Proceedings of the IEEE},\n    doi          = {10.1016/b978-0-08-051584-7.50027-9},\n    keywords     = {computer},\n    mendeley-tags= {computer},\n    pages        = {257--286}\n}\n\n
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\n  \n 1988\n \n \n (4)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n Fingering in haydn's string quartets.\n \n \n \n\n\n \n Drabkin, W.\n\n\n \n\n\n\n Early Music, 16(1): 50–57. 1988.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          drabkin1988-fingering,\n    author       = {Drabkin, William},\n    year         = {1988},\n    title        = {Fingering in haydn's string quartets},\n    doi          = {10.1093/earlyj/XVI.1.50},\n    issn         = {03061078},\n    journal      = {Early Music},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {1},\n    pages        = {50--57},\n    volume       = {16}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Haydn: his life and music.\n \n \n \n\n\n \n Landon, H. C. R.; and Jones, D. W.\n\n\n \n\n\n\n Indiana University Press, Bloomington & Indianapolis, 1988.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             landon.ea1988-haydn,\n    author       = {Landon, Howard Chandler Robbins and Jones, David Wyn},\n    year         = {1988},\n    title        = {Haydn: his life and music},\n    address      = {Bloomington \\& Indianapolis},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    publisher    = {Indiana University Press}\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n A generalized theory of musical contour: its application to melodic and rhythmic analysis of non-tonal music and its perceptual and pedagogical implications.\n \n \n \n \n\n\n \n Marvin, E. W.\n\n\n \n\n\n\n Ph.D. Thesis, University of Rochester, 1988.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@PhDThesis{        marvin1988-generalized,\n    author       = {Marvin, Elizabeth West},\n    year         = {1988},\n    title        = {A generalized theory of musical contour: its application\n                   to melodic and rhythmic analysis of non-tonal music and\n                   its perceptual and pedagogical implications},\n    abstract     = {This dissertation proposes the thesis that abstract\n                   theories of pitch- and set-class structure do not reflect\n                   listeners' aural perception of sounding music as\n                   effectively as theories modelling the articulation of\n                   these underlying structures on the musical surface. This\n                   position is supported by a review of pertinent\n                   music-theoretical and music-psychological research. Based\n                   upon the data collected by various music-psychologists,\n                   published elsewhere but compared and critiqued here, this\n                   study concludes that listeners generally use figural cues\n                   drawn from musical context --- for example, melodic\n                   shapes, changes of direction, relative durationnal\n                   patterns, and so on --- to retain and recognize musical\n                   ideas in short-term memory. These figural cues may be\n                   represented in precise notation and compared with one\n                   another by application and generalization of Robert\n                   Morris's contour theories. Morris's comparison matrix and\n                   contour equivalence relations are introduced here,\n                   followed by this author's generalization of the thwory to\n                   duration space and development of similarity relations for\n                   melodic contours of relative pitch height and rhythmic\n                   contours of relative suration successions. The similarity\n                   relations for musical contours build upon previous wort of\n                   Dabid Lewin, Robert Morris, and John Rahn. While the\n                   efficacy of these theories for modelling perceivable\n                   patterns in musical contexts cannot be proven without\n                   further psychological testing, their applicability to\n                   musical analysis is demonstrated. Analyses drawn form the\n                   music of Bartok, Webern, Berg, and Var{\\`{e}}se illustrate\n                   ways in which melodic and rhythmic contour relationships\n                   may be used to shape a formal scheme to differentiate\n                   melody from accompaniment, to associate musical ideas that\n                   belong to different set classes, and to create unity\n                   throuth varied repetition. The concluding chapter explores\n                   avenues for future work. A section on music-psychological\n                   experimentation offers a critical overview of research in\n                   this area and proposes ideas for future experimentation.\n                   Second, the implications of music-psychological research\n                   for the pedagogy of non-tonal music theory are considered\n                   and a model curriculum for non-tonal music theory\n                   proposed. The dissertation concludes by proposing a number\n                   of ways in which contour theory might be generalized to\n                   other domains and illustrates the application of one such\n                   generalization to the analysis of chord spacing in a piano\n                   work of Luigi Dallapiccola.},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    school       = {University of Rochester},\n    type         = {PhD Dissertation},\n    url          = {http://www.mendeley.com/research/a-generalized-theory-of-musical-contour-its-application-to-melodic-and-rhythmic-analysis-of-nontonal-music-and-its-perceptual-and-pedagogical-implications/}\n}\n\n
\n
\n\n\n
\n This dissertation proposes the thesis that abstract theories of pitch- and set-class structure do not reflect listeners' aural perception of sounding music as effectively as theories modelling the articulation of these underlying structures on the musical surface. This position is supported by a review of pertinent music-theoretical and music-psychological research. Based upon the data collected by various music-psychologists, published elsewhere but compared and critiqued here, this study concludes that listeners generally use figural cues drawn from musical context — for example, melodic shapes, changes of direction, relative durationnal patterns, and so on — to retain and recognize musical ideas in short-term memory. These figural cues may be represented in precise notation and compared with one another by application and generalization of Robert Morris's contour theories. Morris's comparison matrix and contour equivalence relations are introduced here, followed by this author's generalization of the thwory to duration space and development of similarity relations for melodic contours of relative pitch height and rhythmic contours of relative suration successions. The similarity relations for musical contours build upon previous wort of Dabid Lewin, Robert Morris, and John Rahn. While the efficacy of these theories for modelling perceivable patterns in musical contexts cannot be proven without further psychological testing, their applicability to musical analysis is demonstrated. Analyses drawn form the music of Bartok, Webern, Berg, and Varèse illustrate ways in which melodic and rhythmic contour relationships may be used to shape a formal scheme to differentiate melody from accompaniment, to associate musical ideas that belong to different set classes, and to create unity throuth varied repetition. The concluding chapter explores avenues for future work. A section on music-psychological experimentation offers a critical overview of research in this area and proposes ideas for future experimentation. Second, the implications of music-psychological research for the pedagogy of non-tonal music theory are considered and a model curriculum for non-tonal music theory proposed. The dissertation concludes by proposing a number of ways in which contour theory might be generalized to other domains and illustrates the application of one such generalization to the analysis of chord spacing in a piano work of Luigi Dallapiccola.\n
\n\n\n
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\n \n\n \n \n \n \n \n Sonata Forms.\n \n \n \n\n\n \n Rosen, C.\n\n\n \n\n\n\n W. W. Norton & Company, New York and London, Rev. Ed. edition, 1988.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             rosen1988-sonata,\n    author       = {Rosen, Charles},\n    year         = {1988},\n    title        = {Sonata Forms},\n    address      = {New York and London},\n    edition      = {Rev. Ed.},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
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\n  \n 1987\n \n \n (3)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Structural functions in music.\n \n \n \n \n\n\n \n Berry, W.\n\n\n \n\n\n\n Dover Publications, Inc, New York, 1987.\n \n\n\n\n
\n\n\n\n \n \n \"StructuralPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@Book{             berry1987-structural,\n    author       = {Berry, Wallace},\n    year         = {1987},\n    title        = {Structural functions in music},\n    address      = {New York},\n    isbn         = {0486253848},\n    keywords     = {music theory,musical analysis},\n    mendeley-tags= {music theory},\n    publisher    = {Dover Publications, Inc},\n    url          = {http://books.google.com/books?hl=en&lr=&id=J4iXm-uoSRUC&oi=fnd&pg=PR11&dq=Structural+Functions+in+Music&ots=k-2Zkuqv_I&sig=gDaGMcfIa7GyNE2CzlOvrS19w2Q}\n}\n\n
\n
\n\n\n\n
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\n \n\n \n \n \n \n \n \n Relating musical contours: Extensions of a Theory for Contour.\n \n \n \n \n\n\n \n Marvin, E. W.; and Laprade, P. A.\n\n\n \n\n\n\n Journal of Music Theory, 31(2): 225–267. 1987.\n \n\n\n\n
\n\n\n\n \n \n \"RelatingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          marvin.ea1987-relating,\n    author       = {Marvin, Elizabeth West and Laprade, Paul A.},\n    year         = {1987},\n    title        = {Relating musical contours: Extensions of a Theory for\n                   Contour},\n    issn         = {0022-2909},\n    journal      = {Journal of Music Theory},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    number       = {2},\n    pages        = {225--267},\n    publisher    = {JSTOR},\n    url          = {http://www.jstor.org/stable/843709},\n    volume       = {31}\n}\n\n
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\n \n\n \n \n \n \n \n \n Composition with pitch-classes: A theory of compositional design.\n \n \n \n \n\n\n \n Morris, R. D.\n\n\n \n\n\n\n Yale University Press, 1987.\n \n\n\n\n
\n\n\n\n \n \n \"CompositionPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             morris1987-composition,\n    author       = {Morris, Robert Daniel},\n    year         = {1987},\n    title        = {Composition with pitch-classes: A theory of compositional\n                   design},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    publisher    = {Yale University Press},\n    url          = {http://www.getcited.org/pub/102618473}\n}\n\n
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\n  \n 1986\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Form in music: an examination of traditional techniques of musical form and their applications in historical and contemporary styles.\n \n \n \n\n\n \n Berry, W.\n\n\n \n\n\n\n Prentice-Hall, Englewood Cliffs, N.J, 2nd edition, 1986.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@Book{             berry1986-form,\n    author       = {Berry, Wallace},\n    year         = {1986},\n    title        = {Form in music: an examination of traditional techniques\n                   of musical form and their applications in historical and\n                   contemporary styles},\n    address      = {Englewood Cliffs, N.J},\n    edition      = {2nd},\n    isbn         = {0133292851},\n    keywords     = {Musical form,music theory},\n    mendeley-tags= {music theory},\n    pages        = {439},\n    publisher    = {Prentice-Hall}\n}\n\n
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\n \n\n \n \n \n \n \n The Great Haydn Quartets: Their interpretation.\n \n \n \n\n\n \n Keller, H.\n\n\n \n\n\n\n J. M. Dent & Sons Ltd, London, 1 edition, 1986.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@Book{             keller1986-great,\n    author       = {Keller, Hans},\n    year         = {1986},\n    title        = {The Great Haydn Quartets: Their interpretation},\n    address      = {London},\n    archiveprefix= {arXiv},\n    arxivid      = {arXiv:1011.1669v3},\n    edition      = {1},\n    eprint       = {arXiv:1011.1669v3},\n    isbn         = {9788578110796},\n    issn         = {1098-6596},\n    keywords     = {History,Music,haydn},\n    mendeley-tags= {haydn},\n    pmid         = {25246403},\n    publisher    = {J. M. Dent \\& Sons Ltd}\n}\n\n
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\n  \n 1985\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n A Methodology for the Discussion of Contour: Its Application to Schoenberg's Music.\n \n \n \n \n\n\n \n Friedmann, M. L.\n\n\n \n\n\n\n Journal of Music Theory, 29(2): 223–248. 1985.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          friedmann1985-methodology,\n    author       = {Friedmann, Michael L.},\n    year         = {1985},\n    title        = {A Methodology for the Discussion of Contour: Its\n                   Application to Schoenberg's Music},\n    doi          = {10.2307/843614},\n    issn         = {00222909},\n    journal      = {Journal of Music Theory},\n    keywords     = {music contour},\n    mendeley-tags= {music contour},\n    number       = {2},\n    pages        = {223--248},\n    url          = {http://links.jstor.org/sici?sici=0022-2909(198523)29:2%3C223:AMFTDO%3E2.0.CO;2-E&origin=crossref},\n    volume       = {29}\n}\n\n
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\n  \n 1984\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n The theory of Partitions.\n \n \n \n\n\n \n Andrews, G.\n\n\n \n\n\n\n Cambridge University Press, Cambridge, 1984.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Book{             andrews1984-theory,\n    author       = {Andrews, George},\n    year         = {1984},\n    title        = {The theory of Partitions},\n    publisher    = {Cambridge University Press},\n    address      = {Cambridge}\n}\n\n
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\n  \n 1983\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Tonal function and metrical accent: A historical perspective.\n \n \n \n\n\n \n Caplin, W. E.\n\n\n \n\n\n\n Music Theory Spectrum, 5(1): 1–14. 1983.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          caplin1983-tonal,\n    author       = {Caplin, William Earl},\n    year         = {1983},\n    title        = {Tonal function and metrical accent: A historical\n                   perspective},\n    doi          = {10.2307/746092},\n    issn         = {15338339},\n    journal      = {Music Theory Spectrum},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {1},\n    pages        = {1--14},\n    volume       = {5}\n}\n\n
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\n \n\n \n \n \n \n \n \n Erratum: \"melodic accent: experiments and a tentative model\" [J. Acoust. Soc. Am. 71, 1596-1605 (1982)].\n \n \n \n \n\n\n \n Thomassen, J. M.\n\n\n \n\n\n\n The Journal of the Acoustical Society of America, 73(1): 373. jan 1983.\n \n\n\n\n
\n\n\n\n \n \n \"Erratum:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@Article{          thomassen1983-erratum,\n    author       = {Thomassen, Joseph M.},\n    year         = {1983},\n    title        = {Erratum: "melodic accent: experiments and a tentative\n                   model" [J. Acoust. Soc. Am. 71, 1596-1605 (1982)].},\n    issn         = {0001-4966},\n    journal      = {The Journal of the Acoustical Society of America},\n    keywords     = {Humans,Models,Music,Probability,Psychoacoustics,Psychological,music\n                   theory},\n    mendeley-tags= {music theory},\n    month        = {jan},\n    number       = {1},\n    pages        = {373},\n    pmid         = {6826904},\n    url          = {http://www.ncbi.nlm.nih.gov/pubmed/6826904},\n    volume       = {73}\n}\n\n
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\n  \n 1982\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Texture as a Sign in Classic and Early Romantic Music.\n \n \n \n \n\n\n \n Levy, J. M.\n\n\n \n\n\n\n Journal of the American Musicological Society, 35(3): 482–531. oct 1982.\n \n\n\n\n
\n\n\n\n \n \n \"TexturePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          levy1982-texture,\n    author       = {Levy, Janet M.},\n    year         = {1982},\n    title        = {Texture as a Sign in Classic and Early Romantic Music},\n    doi          = {10.2307/830985},\n    issn         = {0003-0139},\n    journal      = {Journal of the American Musicological Society},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    month        = {oct},\n    number       = {3},\n    pages        = {482--531},\n    url          = {https://online.ucpress.edu/jams/article/35/3/482/49237/Texture-as-a-Sign-in-Classic-and-Early-Romantic},\n    volume       = {35}\n}\n\n
\n
\n\n\n\n
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\n \n\n \n \n \n \n \n \n Melodic accent: Experiments and a tentative model.\n \n \n \n \n\n\n \n Thomassen, J. M.\n\n\n \n\n\n\n The Journal of the Acoustical Society of America, 71(6): 1596. 1982.\n \n\n\n\n
\n\n\n\n \n \n \"MelodicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          thomassen1982-melodic,\n    author       = {Thomassen, Joseph M.},\n    year         = {1982},\n    title        = {Melodic accent: Experiments and a tentative model},\n    doi          = {10.1121/1.387814},\n    issn         = {00014966},\n    journal      = {The Journal of the Acoustical Society of America},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    number       = {6},\n    pages        = {1596},\n    url          = {http://link.aip.org/link/JASMAN/v71/i6/p1596/s1&Agg=doi},\n    volume       = {71}\n}\n\n
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\n\n
\n
\n  \n 1981\n \n \n (7)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n The Submediant in Haydn's Development Sections.\n \n \n \n\n\n \n Andrews, H. L.\n\n\n \n\n\n\n In Haydn Studies: Proceedings of the International Haydn Conference, pages 465–471, Washington, DC, 1981. W. W. Norton & Company\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    andrews1981-submediant,\n    author       = {Andrews, Harold L.},\n    year         = {1981},\n    title        = {The Submediant in Haydn's Development Sections},\n    address      = {Washington, DC},\n    booktitle    = {Haydn Studies: Proceedings of the International Haydn\n                   Conference},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    pages        = {465--471},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n LOWESS: A Program for Smoothing Scatterplots by Robust Locally Weighted Regression.\n \n \n \n \n\n\n \n Cleveland, W. S.\n\n\n \n\n\n\n The American Statistician, 35(1): 54. February 1981.\n \n\n\n\n
\n\n\n\n \n \n \"LOWESS:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          cleveland1981-lowess,\n    author       = {Cleveland, William S.},\n    year         = {1981},\n    title        = {{LOWESS}: A Program for Smoothing Scatterplots by Robust\n                   Locally Weighted Regression},\n    volume       = {35},\n    issn         = {00031305},\n    shorttitle   = {LOWESS},\n    url          = {https://www.jstor.org/stable/2683591?origin=crossref},\n    doi          = {10.2307/2683591},\n    language     = {en},\n    number       = {1},\n    urldate      = {2023-04-12},\n    journal      = {The American Statistician},\n    month        = feb,\n    pages        = {54}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Proceedings of the International Haydn Conference.\n \n \n \n\n\n \n Larsen, J. P.; Serwer, H.; and Webster, J.,\n editors.\n \n\n\n \n\n\n\n W. W. Norton & Company, New York and London, 1981.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             larsen.ea1981-proceedings,\n    year         = {1981},\n    title        = {Proceedings of the International Haydn Conference},\n    address      = {New York and London},\n    booktitle    = {Haydn Studies},\n    editor       = {Larsen, Jens Peter and Serwer, Howard and Webster,\n                   James},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Gesture, Form and Syntax in Haydn's Music.\n \n \n \n\n\n \n Levy, J. M.\n\n\n \n\n\n\n In Haydn Studies: Proceedings of the International Haydn Conference, pages 355–363, Washington, DC, 1981. W. W. Norton & Company\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    levy1981-gesture,\n    author       = {Levy, Janet M.},\n    year         = {1981},\n    title        = {Gesture, Form and Syntax in Haydn's Music},\n    address      = {Washington, DC},\n    booktitle    = {Haydn Studies: Proceedings of the International Haydn\n                   Conference},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    pages        = {355--363},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n The Significance of Haydn's Op. 33.\n \n \n \n\n\n \n Moe Jr., O.\n\n\n \n\n\n\n In Haydn Studies: Proceedings of the International Haydn Conference, pages 445–450, Washington, DC, 1981. W. W. Norton & Company\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    moe-jr-1981-significance,\n    author       = {{Moe Jr.}, Orin},\n    year         = {1981},\n    title        = {The Significance of Haydn's Op. 33},\n    address      = {Washington, DC},\n    booktitle    = {Haydn Studies: Proceedings of the International Haydn\n                   Conference},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    pages        = {445--450},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n The alla breve “March”: Its Evolution and Meaning in Haydn's String Quartets.\n \n \n \n\n\n \n Saslav, I.\n\n\n \n\n\n\n In Haydn Studies: Proceedings of the International Haydn Conference, pages 308–314, Washington, DC, 1981. W. W. Norton & Company\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    saslav1981-alla,\n    author       = {Saslav, Isidor},\n    year         = {1981},\n    title        = {The alla breve “March”: Its Evolution and Meaning in\n                   Haydn's String Quartets},\n    address      = {Washington, DC},\n    booktitle    = {Haydn Studies: Proceedings of the International Haydn\n                   Conference},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    pages        = {308--314},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Haydn's Hybrid Variations.\n \n \n \n\n\n \n Sisman, E.\n\n\n \n\n\n\n In Haydn Studies: Proceedings of the International Haydn Conference, pages 509–515, Washington, DC, 1981. W. W. Norton & Company\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InProceedings{    sisman1981-haydns,\n    author       = {Sisman, Elaine},\n    year         = {1981},\n    title        = {Haydn's Hybrid Variations},\n    address      = {Washington, DC},\n    booktitle    = {Haydn Studies: Proceedings of the International Haydn\n                   Conference},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    pages        = {509--515},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
\n
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\n\n
\n
\n  \n 1980\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Classic Music: Expression, Form and Style.\n \n \n \n\n\n \n Ratner, L. G\n\n\n \n\n\n\n Schirmer Books, New York, 1980.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             ratner1980-classic,\n    author       = {Ratner, Leonard G},\n    year         = {1980},\n    title        = {Classic Music: Expression, Form and Style},\n    address      = {New York},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Schirmer Books}\n}\n\n
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\n
\n  \n 1979\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Robust Locally Weighted Regression and Smoothing Scatterplots.\n \n \n \n \n\n\n \n Cleveland, W. S.\n\n\n \n\n\n\n Journal of the American Statistical Association, 74(368): 829–836. December 1979.\n \n\n\n\n
\n\n\n\n \n \n \"RobustPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{          cleveland1979-robust,\n    author       = {Cleveland, William S.},\n    year         = {1979},\n    title        = {{Robust} Locally Weighted Regression and Smoothing\n                   Scatterplots},\n    volume       = {74},\n    issn         = {0162-1459, 1537-274X},\n    url          = {http://www.tandfonline.com/doi/abs/10.1080/01621459.1979.10481038},\n    doi          = {10.1080/01621459.1979.10481038},\n    language     = {en},\n    number       = {368},\n    urldate      = {2023-04-12},\n    journal      = {Journal of the American Statistical Association},\n    month        = dec,\n    pages        = {829--836}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n The Beethoven Quartets.\n \n \n \n\n\n \n Kerman, J.\n\n\n \n\n\n\n WW Norton & Company, New York, NY, 1979.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             kerman1979-beethoven,\n    author       = {Kerman, Joseph},\n    year         = {1979},\n    title        = {The Beethoven Quartets},\n    address      = {New York, NY},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {WW Norton \\& Company}\n}\n\n
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\n  \n 1977\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n The Bass Part in Haydn's Early String Quartets.\n \n \n \n \n\n\n \n Webster, J.\n\n\n \n\n\n\n The Musical Quarterly, 63(3): 390–424. 1977.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          webster1977-bass,\n    author       = {Webster, James},\n    year         = {1977},\n    title        = {The Bass Part in Haydn's Early String Quartets},\n    issn         = {0264-1615},\n    journal      = {The Musical Quarterly},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    number       = {3},\n    pages        = {390--424},\n    url          = {https://www.jstor.org/stable/pdf/741433.pdf},\n    volume       = {63}\n}\n\n
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\n  \n 1976\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n The Theory of Partitions.\n \n \n \n\n\n \n Andrews, G. E.\n\n\n \n\n\n\n Volume 2 of Encyclopedia of Mathematics and its ApplicationsAddison-Wesley Publishing Company, London, 1976.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Book{             andrews1976-theory,\n    author       = {Andrews, George E.},\n    year         = {1976},\n    title        = {The {Theory} of {Partitions}},\n    address      = {London},\n    series       = {Encyclopedia of {Mathematics} and its {Applications}},\n    volume       = {2},\n    language     = {en},\n    publisher    = {Addison-Wesley Publishing Company},\n    editor       = {Turán, Paul}\n}\n\n
\n
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\n \n\n \n \n \n \n \n Musical Form: Studies in analysis and synthesis.\n \n \n \n\n\n \n Kohs, E. B.\n\n\n \n\n\n\n Houghton Mifflin, Boston, 1976.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             kohs1976-musical,\n    author       = {Kohs, Ellis Bonoff},\n    year         = {1976},\n    title        = {Musical Form: Studies in analysis and synthesis},\n    address      = {Boston},\n    keywords     = {music theory},\n    mendeley-tags= {music theory},\n    publisher    = {Houghton Mifflin}\n}\n\n
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\n  \n 1975\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n The Chronology of Haydn's String Quartets.\n \n \n \n\n\n \n Webster, J.\n\n\n \n\n\n\n The Musical Quarterly, 61(1): 17–46. 1975.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n
@Article{          webster1975-chronology,\n    author       = {Webster, James},\n    year         = {1975},\n    title        = {The Chronology of Haydn's String Quartets},\n    journal      = {The Musical Quarterly},\n    keywords     = {haydn,music history},\n    mendeley-tags= {haydn,music history},\n    number       = {1},\n    pages        = {17--46},\n    volume       = {61}\n}\n\n
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\n  \n 1974\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Joseph Haydn and the String quartet.\n \n \n \n\n\n \n Barrett-Ayres, R.\n\n\n \n\n\n\n Schirmer Books, New York, 1974.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             barrett-ayres1974-joseph,\n    author       = {Barrett-Ayres, Reginald},\n    year         = {1974},\n    title        = {Joseph Haydn and the String quartet},\n    address      = {New York},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    publisher    = {Schirmer Books}\n}\n\n
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\n \n\n \n \n \n \n \n Haydn.\n \n \n \n\n\n \n Hughes, R.\n\n\n \n\n\n\n J. M. Dent & Sons Ltd, London, 1974.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Book{             hughes1974-haydn,\n    author       = {Hughes, Rosemary},\n    year         = {1974},\n    title        = {Haydn},\n    address      = {London},\n    keywords     = {haydn},\n    mendeley-tags= {haydn},\n    publisher    = {J. M. Dent \\& Sons Ltd}\n}\n\n
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\n  \n 1973\n \n \n (2)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n The Rise of Chamber Music.\n \n \n \n\n\n \n Geiringer, K.\n\n\n \n\n\n\n In Wellesz, E.; and Sternfeld, F. W, editor(s), The New Oxford history of music. Vol. 7, Age of enlightenment 1745-1790, IX, pages 515–573. Oxford University Press, Oxford, 1973.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@InCollection{     geiringer1973-rise,\n    author       = {Geiringer, Karl},\n    year         = {1973},\n    title        = {The Rise of Chamber Music},\n    address      = {Oxford},\n    booktitle    = {The New Oxford history of music. Vol. 7, Age of\n                   enlightenment 1745-1790},\n    chapter      = {IX},\n    editor       = {Wellesz, Egon and Sternfeld, Frederick W},\n    isbn         = {0 19 316307 1},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    pages        = {515--573},\n    publisher    = {Oxford University Press}\n}\n\n
\n
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\n \n\n \n \n \n \n \n Chamber Music, Divertimento, Serenade.\n \n \n \n\n\n \n Pauly, R. G.\n\n\n \n\n\n\n In Music in the classic period, 9, pages 140–158. Prentice-Hall, Englewood Cliffs, NJ, 1973.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@InCollection{     pauly1973-chamber,\n    author       = {Pauly, Reinhard G.},\n    year         = {1973},\n    title        = {Chamber Music, Divertimento, Serenade},\n    address      = {Englewood Cliffs, NJ},\n    booktitle    = {Music in the classic period},\n    chapter      = {9},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    pages        = {140--158},\n    publisher    = {Prentice-Hall}\n}\n\n
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\n  \n 1970\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Beethoven's Contrapuntal Studies with Haydn.\n \n \n \n \n\n\n \n Mann, A.\n\n\n \n\n\n\n The Musical Quarterly, 56(4): 711–726. 1970.\n \n\n\n\n
\n\n\n\n \n \n \"Beethoven'sPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n
@Article{          mann1970-beethovens,\n    author       = {Mann, Alfred},\n    year         = {1970},\n    title        = {Beethoven's Contrapuntal Studies with Haydn},\n    journal      = {The Musical Quarterly},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {4},\n    pages        = {711--726},\n    url          = {http://www.jstor.org/stable/740934},\n    volume       = {56}\n}\n\n
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\n  \n 1969\n \n \n (1)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n Thematic Profile and Character in the Quartet-Finales of Joseph Haydn (A Contribution to the Micro-Analysis of Thematic Structure).\n \n \n \n\n\n \n Bartha, D.\n\n\n \n\n\n\n Studia Musicologica Academiae Scientiarum Hungaricae, 11(1/4): 35–62. 1969.\n \n\n\n\n
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@Article{          bartha1969-thematic,\n    author       = {Bartha, D{\\'{e}}nes},\n    year         = {1969},\n    title        = {Thematic Profile and Character in the Quartet-Finales of\n                   Joseph Haydn (A Contribution to the Micro-Analysis of\n                   Thematic Structure)},\n    doi          = {10.2307/901267},\n    issn         = {00393266},\n    journal      = {Studia Musicologica Academiae Scientiarum Hungaricae},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1/4},\n    pages        = {35--62},\n    volume       = {11}\n}\n\n
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\n  \n 1961\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Register and the Large-Scale Connection.\n \n \n \n\n\n \n Oster, E.\n\n\n \n\n\n\n Journal of Music Theory, 5(1): 54. 1961.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          oster1961-register,\n    author       = {Oster, Ernst},\n    year         = {1961},\n    title        = {Register and the Large-Scale Connection},\n    doi          = {10.2307/842870},\n    issn         = {00222909},\n    journal      = {Journal of Music Theory},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {54},\n    volume       = {5}\n}\n\n
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\n  \n 1957\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Joseph Haydn: thematisch-bibliographisches Werkverzeichnis.\n \n \n \n \n\n\n \n van Hoboken, A.\n\n\n \n\n\n\n Schott & Co., Ltd., Mainz, 1957.\n \n\n\n\n
\n\n\n\n \n \n \"JosephPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             hoboken1957-joseph,\n    author       = {van Hoboken, Anthony},\n    year         = {1957},\n    title        = {Joseph Haydn: thematisch-bibliographisches\n                   Werkverzeichnis},\n    address      = {Mainz},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {Schott \\& Co., Ltd.},\n    url          = {https://archive.org/details/JosephHaydnThematisch-bibliographischesWerkverzeichnis}\n}\n\n
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\n  \n 1950\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Ambiguity in the string quartets of Joseph Haydn.\n \n \n \n \n\n\n \n Silbert, D.\n\n\n \n\n\n\n Musical Quarterly, 36(1): 562—-573. 1950.\n \n\n\n\n
\n\n\n\n \n \n \"AmbiguityPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Article{          silbert1950-ambiguity,\n    author       = {Silbert, Doris},\n    year         = {1950},\n    title        = {Ambiguity in the string quartets of Joseph Haydn},\n    doi          = {10.1093/mq/XXXVI.4.562},\n    journal      = {Musical Quarterly},\n    keywords     = {music analysis},\n    mendeley-tags= {music analysis},\n    number       = {1},\n    pages        = {562----573},\n    url          = {http://mq.oxfordjournals.org/content/XXXVI/4/562.extract},\n    volume       = {36}\n}\n\n
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\n  \n 1946\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Haydn: a creative life in Music.\n \n \n \n\n\n \n Geiringer, K.\n\n\n \n\n\n\n W. W. Norton & Company, New York, 1946.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@Book{             geiringer1946-haydn,\n    author       = {Geiringer, Karl},\n    year         = {1946},\n    title        = {Haydn: a creative life in Music},\n    address      = {New York},\n    keywords     = {music history},\n    mendeley-tags= {music history},\n    publisher    = {W. W. Norton \\& Company}\n}\n\n
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\n  \n 1928\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Limiting forms of the frequency distribution of the largest or smallest member of a sample.\n \n \n \n\n\n \n Fisher, R. A.; and Tippett, L. H.\n\n\n \n\n\n\n Mathematical Proceedings of the Cambridge Philosophical Society, 24(2): 180–190. 1928.\n \n\n\n\n
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@Article{          fisher.ea1928-limiting,\n    author       = {Fisher, R. A. and Tippett, L. H.C.},\n    year         = {1928},\n    title        = {Limiting forms of the frequency distribution of the\n                   largest or smallest member of a sample},\n    doi          = {10.1017/S0305004100015681},\n    issn         = {14698064},\n    journal      = {Mathematical Proceedings of the Cambridge Philosophical\n                   Society},\n    keywords     = {mathematics},\n    mendeley-tags= {mathematics},\n    number       = {2},\n    pages        = {180--190},\n    volume       = {24}\n}\n\n
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