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Single-channel mixture decomposition using Bayesian harmonic models

Abstract : We consider the source separation problem for single-channel music signals. After a brief review of existing methods, we focus on decomposing a mixture into components made of harmonic sinusoidal partials. We address this problem in the Bayesian framework by building a probabilistic model of the mixture combining generic priors for harmonicity, spectral envelope, note duration and continuity. Experiments suggest that the derived blind decomposition method leads to better separation results than nonnegative matrix factorization for certain mixtures.
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Submitted on : Wednesday, December 8, 2010 - 4:08:35 PM
Last modification on : Thursday, March 21, 2019 - 2:20:03 PM
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  • HAL Id : inria-00544663, version 1


Emmanuel Vincent, Mark Plumbley. Single-channel mixture decomposition using Bayesian harmonic models. 6th Int. Conf. on Independent Component Analysis and Blind Source Separation (ICA), Mar 2006, Charleston, United States. pp.722--730. ⟨inria-00544663⟩



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