On spectral basis selection for single channel polyphonic music separation

Authors:
Minje Kim;Seungjin Choi
Affiliations:
Department of Computer Science, Pohang University of Science and Technology, Pohang, Korea;Department of Computer Science, Pohang University of Science and Technology, Pohang, Korea
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

Citing 2
Cited 1

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The Journal of Machine Learning Research
Nonnegative features of spectro-temporal sounds for classification

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Monaural music source separation: nonnegativity, sparseness, and shift-invariance

ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation

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Abstract

In this paper we present a method of separating musical instrument sound sources from their monaural mixture, where we take the harmonic structure of music into account and use the sparseness and the overlapping NMF to select representative spectral basis vectors which are used to reconstruct unmixed sound. A method of spectral basis selection is illustrated and experimental results with monaural instantaneous mixtures of voice/cello and saxophone/viola, are shown to confirm the validity of our proposed method.