Fast bayesian NMF algorithms enforcing harmonicity and temporal continuity in polyphonic music transcription

Nancy Bertin, Roland Badeau, Emmanuel Vincent

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article presents theoretical and experimental results about constrained non-negative matrix factorization (NMF) in a Bayesian framework, enforcing both spectral harmonicity and temporal continuity. We exhibit fast multiplicative update rules to perform the decomposition, which are then applied to perform polyphonic piano music transcription. This approach is shown to outperform other standard NMF-based transcription systems, providing a meaningful mid-level representation of the data.

Original languageEnglish
Title of host publication2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2009
Pages29-32
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2009 - New Paltz, NY, United States
Duration: 18 Oct 200921 Oct 2009

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Conference

Conference2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2009
Country/TerritoryUnited States
CityNew Paltz, NY
Period18/10/0921/10/09

Keywords

  • Audio source separation
  • Bayesian regression
  • Music transcription
  • Non-negative Matrix Factorization (NMF)

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