Audio genre classification using percussive pattern clustering combined with timbral features
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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This paper discusses an approach to extract constituent percussive bar-long patterns in a music piece given as acoustic signal and to analyze the music structure with a map of constituent rhythmic patterns. Possible applications include music genre classification, music information retrieval (MIR) and music modification such as replacing rhythmic patterns with others. We propose a mathematical method based on One-pass DP algorithm and k-means clustering to extract unit percussive rhythmic patterns. As the result of identifying and localization the unit patterns in the entire piece, we obtained a music structure in the form of a map of rhythmic patterns.