Music summarization using key phrases

  • Authors:

  • B. Logan;S. Chu

  • Affiliations:

  • Res. Labs., Compaq Comput. Corp., Cambridge, MA, USA;-

  • Venue:
  • ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
  • Year:
  • 2000

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Abstract

Systems to automatically provide a representative summary or 'key phrase' of a piece of music are described. For a 'rock' song with 'verse' and 'chorus' sections, we aim to return the chorus or in any case the most repeated and hence most memorable section. The techniques are less applicable to music with more complicated structure although possibly our general framework could still be used with different heuristics. Our process consists of three steps. First we parameterize the song into features. Next we use these features to discover the song structure, either by clustering fixed-length segments or by training a hidden Markov model (HMM) for the song. Finally, given this structure, we use heuristics to choose the key phrase. Results for summaries of 18 Beatles songs evaluated by ten users show that the technique based on clustering is superior to the HMM approach and to choosing the key phrase at random.