@InProceedings{    lascabettes.ea2022-computational,
    author       = {Lascabettes, Paul and Agon, Carlos and Andreatta, Moreno
                   and Bloch, Isabelle},
    year         = {2022},
    title        = {Computational Analysis of Musical Structures based on
                   Morphological Filters},
    abstract     = {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:},
    address      = {Atlanta, USA},
    booktitle    = {MCM 2022 - 8th International Conference Mathematics and
                   Computation in Music},
    keywords     = {Chord contour,Mathematical morphology,Music
                   structure,Self-distance matrix,Symbolic Music information
                   research,music and mathematics},
    mendeley-tags= {music and mathematics},
    url          = {https://hal.archives-ouvertes.fr/hal-03641511/}
}

{"_id":"P8rwrcmoaHDqWbYDe","bibbaseid":"lascabettes-agon-andreatta-bloch-computationalanalysisofmusicalstructuresbasedonmorphologicalfilters-2022","author_short":["Lascabettes, P.","Agon, C.","Andreatta, M.","Bloch, I."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Lascabettes"],"firstnames":["Paul"],"suffixes":[]},{"propositions":[],"lastnames":["Agon"],"firstnames":["Carlos"],"suffixes":[]},{"propositions":[],"lastnames":["Andreatta"],"firstnames":["Moreno"],"suffixes":[]},{"propositions":[],"lastnames":["Bloch"],"firstnames":["Isabelle"],"suffixes":[]}],"year":"2022","title":"Computational Analysis of Musical Structures based on Morphological Filters","abstract":"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:","address":"Atlanta, USA","booktitle":"MCM 2022 - 8th International Conference Mathematics and Computation in Music","keywords":"Chord contour,Mathematical morphology,Music structure,Self-distance matrix,Symbolic Music information research,music and mathematics","mendeley-tags":"music and mathematics","url":"https://hal.archives-ouvertes.fr/hal-03641511/","bibtex":"@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","author_short":["Lascabettes, P.","Agon, C.","Andreatta, M.","Bloch, I."],"key":"lascabettes.ea2022-computational","id":"lascabettes.ea2022-computational","bibbaseid":"lascabettes-agon-andreatta-bloch-computationalanalysisofmusicalstructuresbasedonmorphologicalfilters-2022","role":"author","urls":{"Paper":"https://hal.archives-ouvertes.fr/hal-03641511/"},"keyword":["Chord contour","Mathematical morphology","Music structure","Self-distance matrix","Symbolic Music information research","music and mathematics"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://hmb.sampaio.me/bibliografia.bib.txt","dataSources":["n6MFY2CscQLDpJ7nT"],"keywords":["chord contour","mathematical morphology","music structure","self-distance matrix","symbolic music information research","music and mathematics"],"search_terms":["computational","analysis","musical","structures","based","morphological","filters","lascabettes","agon","andreatta","bloch"],"title":"Computational Analysis of Musical Structures based on Morphological Filters","year":2022}