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    (Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

    Musical genres: beating to the rhythms of different drums

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    Correa, Debora C.1; Saito, Jose H.2; Costa, Luciano da F.1


    1Univ Sao Paulo. Inst Fis Sao Carlos

    2Univ Fed Sao Carlos. Dept Computacao

    Document type: Journal article
    Source: NEW JOURNAL OF PHYSICS; v. 12, MAY 20 2010.
    Web of Science Citations: 6
    Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method. (AU)

    FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
    Awardee:Roberto Marcondes Cesar Junior
    Support type: Research Projects - Thematic Grants
    CDi/FAPESP - Documentation and Information Center, The State of São Paulo Research Foundation

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