The Journal of the Acoustical Society of Korea

The Acoustical Society of Korea (한국음향학회)
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Automatic Emotion Classification of Music Signals Using MDCT-Driven Timbre and Tempo Features

  • Kim, Hyoung-Gook (Samsung Advanced Institute of Technology Computing Lab) ;
  • Eom, Ki-Wan (Samsung Advanced Institute of Technology Computing Lab)
  • Published : 2006.06.01
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Abstract

This paper proposes an effective method for classifying emotions of the music from its acoustical signals. Two feature sets, timbre and tempo, are directly extracted from the modified discrete cosine transform coefficients (MDCT), which are the output of partial MP3 (MPEG 1 Layer 3) decoder. Our tempo feature extraction method is based on the long-term modulation spectrum analysis. In order to effectively combine these two feature sets with different time resolution in an integrated system, a classifier with two layers based on AdaBoost algorithm is used. In the first layer the MDCT-driven timbre features are employed. By adding the MDCT-driven tempo feature in the second layer, the classification precision is improved dramatically.

Keywords

References

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