TR2003-139

Non-Negative Matrix Factorization for Polyphonic Music Transcription


Abstract:

In this paper we present a methodology for analyzing polyphonic musical passages comprised by notes that exhibit a harmonically fixed spectral profile (such as piano notes). Taking advantage of this unique note structure we can model the audio content of the musical passage by a linear basis transform and use non-negative matrix decomposition methods to estimate the spectral profile and the temporal information of every note. This approach results in a very simple and compact system that is not knowledge based, but rather learns notes by observation.

 

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    •  NEWS    WASPAA 2003: 2 publications by MERL researchers and others
      Date: October 20, 2003
      Where: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
      Brief
      • The papers "Non-negative Matrix Factorization for Polyphonic Music Transcription" by Smaragdis, P. and Brown, J.C. and "Multi-Channel Source Separation by Beamforming Trained with Factorial HMMS" by Reyes-Gomez, M.J., Raj, B. and Ellis, D.P.W. were presented at the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA).
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