Blind signal decompositions for automatic transcription of polyphonic music: NMF and K-SVD on the benchmark

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Abstract

This paper investigates on the behavior of two blind signal decomposition algorithms, non negative matrix factorization (NMF) and non, negative K-SVD (NKSVD), in a polyphonic music transcription, task. State-of-the-art transcription systems are based on a frame-by-frame, low-level approach; blind systems could be an alternative to them. Two raw but effective audio-to-MIDI systems are proposed and evaluated. Performances are similar, but in favor of NMF, which is more robust to initialization, choice of the order and computationnally less costly.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PagesI65-I68
DOIs
Publication statusPublished - 6 Aug 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: 15 Apr 200720 Apr 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume1
ISSN (Print)1520-6149

Conference

Conference2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/TerritoryUnited States
CityHonolulu, HI
Period15/04/0720/04/07

Keywords

  • Automatic transcription
  • K-SVD
  • Non negative matrix factorization
  • Polyphonic music

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