• DocumentCode
    2936760
  • Title

    Music Genre Classification Based on Entropy and Fractal Lacunarity

  • Author

    Goulart, Antonio Jose Homsi ; Maciel, Carlos Dias ; Guido, Rodrigo Capobianco ; Paulo, Katia Cristina Silva ; Silva, Ivan Nunes da

  • Author_Institution
    Sch. of Eng. at Sao Carlos, Univ. of Sao Paulo, Sao Carlos, Brazil
  • fYear
    2011
  • fDate
    5-7 Dec. 2011
  • Firstpage
    533
  • Lastpage
    536
  • Abstract
    In this letter, we present an automatic music genre classification scheme based on a Gaussian Mixture Model (GMM) classifier. The proposed technique adopts entropies and lacunarities as features for the classifications. Tests were carried out with four styles of Brazilian music, namely Axe, Bossa Nova, Forro, and Samba.
  • Keywords
    Gaussian processes; audio signal processing; entropy; music; Axe; Bossa Nova; Brazilian music; Forro; Gaussian mixture model classifier; Samba; automatic music genre classification; entropy; fractal lacunarity; Accuracy; Entropy; Feature extraction; Fractals; Humans; Music; Training; GMM; automatic music genre classification; entropy; lacunarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia (ISM), 2011 IEEE International Symposium on
  • Conference_Location
    Dana Point CA
  • Print_ISBN
    978-1-4577-2015-4
  • Type

    conf

  • DOI
    10.1109/ISM.2011.94
  • Filename
    6123402