• DocumentCode
    259653
  • Title

    Supervised Music Chord Recognition

  • Author

    Rida, Imad ; Herault, Romain ; Gasso, Gilles

  • Author_Institution
    INSA de Rouen, Normandie Univ., St. Étienne-du-Rouvray, France
  • fYear
    2014
  • fDate
    3-6 Dec. 2014
  • Firstpage
    336
  • Lastpage
    341
  • Abstract
    Chord represents the back-bone of occidental music genre as it contains rich harmonic information which is useful for various music applications such as music genre classification or music retrieval. Hence, chord recognition or transcription is of importance for music representation. In this paper we focus on chord recognition and especially investigate different features representation used in such a system: classical features as well as a new type of feature we propose are explored. We evaluate their usefulness through a multi-class chord classification problem.
  • Keywords
    music; feature representation; harmonic information; multiclass chord classification; music representation; music retrieval; occidental music genre classification; supervised music chord recognition; Feature extraction; Harmonic analysis; Hidden Markov models; Kernel; Spectrogram; Training; Vectors; Music; chord; feature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2014 13th International Conference on
  • Conference_Location
    Detroit, MI
  • Type

    conf

  • DOI
    10.1109/ICMLA.2014.60
  • Filename
    7033137