• DocumentCode
    2695316
  • Title

    Automatic chord recognition for music classification and retrieval

  • Author

    Cheng, Heng-Tze ; Yang, Yi-Hsuan ; Lin, Yu-Ching ; Liao, I-Bin ; Chen, Homer H.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei
  • fYear
    2008
  • fDate
    June 23 2008-April 26 2008
  • Firstpage
    1505
  • Lastpage
    1508
  • Abstract
    As one of the most important mid-level features of music, chord contains rich information of harmonic structure that is useful for music information retrieval. In this paper, we present a chord recognition system based on the N-gram model. The system is time-efficient, and its accuracy is comparable to existing systems. We further propose a new method to construct chord features for music emotion classification and evaluate its performance on commercial song recordings. Experimental results demonstrate the advantage of using chord features for music classification and retrieval.
  • Keywords
    audio signal processing; emotion recognition; information retrieval; music; pattern classification; signal classification; N-gram model; automatic chord recognition; commercial song recordings; music classification; music emotion classification; music information retrieval; Hidden Markov models; Histograms; Information analysis; Laboratories; Mel frequency cepstral coefficient; Multimedia systems; Multiple signal classification; Music information retrieval; Statistics; Telecommunications; Chord; N-gram; music classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2008 IEEE International Conference on
  • Conference_Location
    Hannover
  • Print_ISBN
    978-1-4244-2570-9
  • Electronic_ISBN
    978-1-4244-2571-6
  • Type

    conf

  • DOI
    10.1109/ICME.2008.4607732
  • Filename
    4607732