@InProceedings{    rodriguez-lopez.ea2014-symbolic,
    author       = {Rodr{\'{i}}guez-L{\'{o}}pez, Marcelo and Volk, Anja},
    year         = {2014},
    title        = {Symbolic Segmentation: A Corpus-Based Analysis of Melodic
                   Phrases},
    abstract     = {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.},
    address      = {Cham},
    booktitle    = {Proc. 10th International Symposium on Computer Music
                   Multidisciplinary Research (CMMR)},
    editor       = {Aramaki, Mitsuko and Derrien, Olivier and
                   Kronland-Martinet, Richard and Ystad, S{\o}lvi},
    isbn         = {978-3-319-12976-1},
    keywords     = {Interval Size,Music Information Retrieval,Phrase
                   Boundary,Pitch Interval,Segmentation Model,music
                   information retrieval},
    mendeley-tags= {music information retrieval},
    pages        = {548--557},
    publisher    = {Springer International Publishing},
    url          = {https://link.springer.com/chapter/10.1007/978-3-319-12976-1_33}
}

{"_id":"ge2BC6rrJw6Sq6S44","bibbaseid":"rodriguezlpez-volk-symbolicsegmentationacorpusbasedanalysisofmelodicphrases-2014","authorIDs":[],"author_short":["Rodríguez-López, M.","Volk, A."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Rodríguez-López"],"firstnames":["Marcelo"],"suffixes":[]},{"propositions":[],"lastnames":["Volk"],"firstnames":["Anja"],"suffixes":[]}],"year":"2014","title":"Symbolic Segmentation: A Corpus-Based Analysis of Melodic Phrases","abstract":"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.","address":"Cham","booktitle":"Proc. 10th International Symposium on Computer Music Multidisciplinary Research (CMMR)","editor":[{"propositions":[],"lastnames":["Aramaki"],"firstnames":["Mitsuko"],"suffixes":[]},{"propositions":[],"lastnames":["Derrien"],"firstnames":["Olivier"],"suffixes":[]},{"propositions":[],"lastnames":["Kronland-Martinet"],"firstnames":["Richard"],"suffixes":[]},{"propositions":[],"lastnames":["Ystad"],"firstnames":["Sølvi"],"suffixes":[]}],"isbn":"978-3-319-12976-1","keywords":"Interval Size,Music Information Retrieval,Phrase Boundary,Pitch Interval,Segmentation Model,music information retrieval","mendeley-tags":"music information retrieval","pages":"548–557","publisher":"Springer International Publishing","url":"https://link.springer.com/chapter/10.1007/978-3-319-12976-1_33","bibtex":"@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","author_short":["Rodríguez-López, M.","Volk, A."],"editor_short":["Aramaki, M.","Derrien, O.","Kronland-Martinet, R.","Ystad, S."],"key":"rodriguez-lopez.ea2014-symbolic","id":"rodriguez-lopez.ea2014-symbolic","bibbaseid":"rodriguezlpez-volk-symbolicsegmentationacorpusbasedanalysisofmelodicphrases-2014","role":"author","urls":{"Paper":"https://link.springer.com/chapter/10.1007/978-3-319-12976-1_33"},"keyword":["Interval Size","Music Information Retrieval","Phrase Boundary","Pitch Interval","Segmentation Model","music information retrieval"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://hmb.sampaio.me/bibliografia.bib.txt","creationDate":"2019-08-08T23:06:47.424Z","downloads":0,"keywords":["interval size","music information retrieval","phrase boundary","pitch interval","segmentation model","music information retrieval"],"search_terms":["symbolic","segmentation","corpus","based","analysis","melodic","phrases","rodríguez-lópez","volk"],"title":"Symbolic Segmentation: A Corpus-Based Analysis of Melodic Phrases","year":2014,"dataSources":["n6MFY2CscQLDpJ7nT","RFLDZw5KyJdadDXDm"]}