Content-based methods for the management of digital music

  • Authors:
  • D. Pye

  • Affiliations:
  • AT&TLabs., Cambridge, UK

  • Venue:
  • ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
  • Year:
  • 2000

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Abstract

The literature on content-based music retrieval has largely finessed acoustic issues by using MIDI format music. This paper however considers content-based classification and retrieval of a typical (MPEG layer III) digital music archive. Two statistical techniques are investigated and appraised. Gaussian mixture modelling performs well with an accuracy of 92% on a music classification task. A tree-based vector quantization scheme offers marginally worse performance in a faster, scalable framework. Good results are also reported for music retrieval-by-similarity using the same techniques. Mel-frequency cepstral coefficients parameterize the audio well, though are slow to compute from the compressed domain. A new parameterization (MP3CEP), based on a partial decompression of MPEG layer III audio, is therefore proposed to facilitate music processing at user-interactive speeds. Overall, the techniques described provide useful tools in the management of a typical digital music library.