Non-Negative Matrix Factorization for Polyphonic Music Transcription


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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@inproceedings{Smaragdis2003NonNegativeMF, title={Non-Negative Matrix Factorization for Polyphonic Music Transcription}, author={Paris Smaragdis and Judith C. Brown}, year={2003} }