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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Least squares formulation of robust nonnegative factor analysis

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  • 1997
1 Excerpt

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1 Excerpt
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