A singer identification technique for content-based classification of MP3 music objects

ABSTRACT

As there is a growing amount of MP3 music data available on the Internet today, the problems related to music classification and content-based music retrieval are getting more attention recently. In this paper, we propose an approach to automatically classify MP3 music objects according to their singers. First, the coefficients extracted from the output of the polyphase filters are used to compute the MP3 features for segmentation. Based on these features, an MP3 music object can be decomposed into a sequence of notes (or phonemes). Then for each MP3 phoneme in the training set, its MP3 feature is extracted and used to train an MP3 classifier which can identify the singer of an unknown MP3 music object. Experiments are performed and analyzed to show the effectiveness of the proposed method.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Selection process; Search process

General Terms:
Algorithms, Design, Documentation, Experimentation, Measurement, Performance

Keywords:
MP3, MP3 classification, MP3 databases, content-based music classification, music classification, music databases, music feature extraction, singer identification