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The Classification of Music Styles on the Basis of Spectral Contrast Features

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초록

In this paper, we propose that the contrast features of octave spectrum can be used to show spectral contrast features of some music clips. It shows the relative spectral distribution rather than average spectrum. From the experiment, it can be seen the method of spectral contrast features has a good performance in classification of music styles. Another comparative experiment shows that the method of spectral contrast features can better distinguish different music styles than the method of MFCC features that commonly used previously in the classification system of music styles.

Abstract

In this paper, we propose that the contrast features of octave spectrum can be used to show spectral contrast features of some music clips. It shows the relative spectral distribution rather than average spectrum. From the experiment, it can be seen the method of spectral contrast features has a good performance in classification of music styles. Another comparative experiment shows that the method of spectral contrast features can better distinguish different music styles than the method of MFCC features that commonly used previously in the classification system of music styles.

참고문헌 (9)

  1. D.Li, "Classification of General Audio Data for Content—Based Retrieval", Pattern Recognition Letters, 22(t), pp.533~544 (2010)
  2. Yao Qi, "The Analysis of Rhythm Art Characteristics in the Movie Picture", Movie Literature, pp.29~31 (2013)
  3. Dong Ruijuan, "The Sutdy of Normal Range of Music Assessment System", Journal of Clinical Otolaryngology Head and Neck Surgery, pp.712~716 (2013)
  4. Zhao Can, "Rhythm of Footage", Youth Journalist, 83(94), pp.83~94 (2012)
  5. Gao Yumin, "The Design of Music Broadcast System based on PIC Microcontroller in PWM Mode", Measurement and Control Technology, pp.72~75 (2014)
  6. qZhen Lidong, "Computer and Network" (2012)
  7. Han Li, "Study on High Resolution Full Spectrum Decomposition" (2013), Ji Lin University
  8. Li Jian, "Application Research on Neural Network in Music Classification" (2010), Computer Simulation
  9. Tian Hui, "Application of Support Vector Machine (SVM) Ensemble in Music Classification" (2009), Shandong Normal University

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