• DocumentCode
    2294416
  • Title

    Music type classification by spectral contrast feature

  • Author

    Dan-ning Jiang ; Lu, Lie ; Zhang, Hong-Jiang ; Tao, Jian-Hua ; Lian-Hong Cai

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
  • Volume
    1
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    113
  • Abstract
    Automatic music type classification is very helpful for the management of digital music databases. In this paper, the octave-based spectral contrast feature is proposed to represent the spectral characteristics of a music clip. It represented the relative spectral distribution instead of average spectral envelope. Experiments show that the octave-based spectral contrast feature performs well in music type classification. Another comparison experiment demonstrates that the octave-based spectral contrast feature has a better discrimination among different music types than mel-frequency cepstral coefficients (MFCC), which is often used in previous music type classification systems.
  • Keywords
    feature extraction; multimedia databases; music; pattern classification; spectral analysis; automatic music type classification; digital music databases; music clip; octave-based spectral contrast feature; relative spectral distribution; spectral characteristics representation; Asia; Cepstral analysis; Computer science; Hidden Markov models; History; Mel frequency cepstral coefficient; Modems; Multiple signal classification; Spatial databases; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
  • Print_ISBN
    0-7803-7304-9
  • Type

    conf

  • DOI
    10.1109/ICME.2002.1035731
  • Filename
    1035731