HAL : hal-00482223, version 1

DOI : 10.1007/978-3-642-00599-2_97

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8th Int. Conf. on Independent Component Analysis and Signal Separation (ICA), Paraty : Brésil (2009)

Underdetermined instantaneous audio source separation via local Gaussian modeling

Emmanuel Vincent 1, Simon Arberet 1, Rémi Gribonval 1

(2009)

Underdetermined source separation is often carried out by modeling time-frequency source coefficients via a fixed sparse prior. This approach fails when the number of active sources in one time-frequency bin is larger than the number of channels or when active sources lie on both sides of an inactive source. In this article, we partially address these issues by modeling time-frequency source coefficients via Gaussian priors with free variances. We study the resulting maximum likelihood criterion and derive a fast non-iterative optimization algorithm that finds the global minimum. We show that this algorithm outperforms state-of-the- art approaches over stereo instantaneous speech mixtures.

1 :	METISS (INRIA - IRISA)
	CNRS : UMR6074 – INRIA – Institut National des Sciences Appliquées (INSA) - Rennes – Université de Rennes 1

Domaine

:

Sciences de l'ingénieur/Traitement du signal et de l'image Informatique/Traitement du signal et de l'image

Mots Clés : underdetermined – source separation – Gaussian modeling – algorithm

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Contributeur : Emmanuel Vincent <>

Soumis le : Lundi 10 Mai 2010, 09:18:18

Dernière modification le : Mercredi 8 Décembre 2010, 17:37:44