Under-determined source separation: comparison of two approaches based on sparse decompositions

Sylvain Lesage 1 Sacha Krstulovic 1 Rémi Gribonval 1
1 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper focuses on under-determined source separation when the mixing parameters are known. The approach is based on a sparse decomposition of the mixture. In the proposed method, the mixture is decomposed with Matching Pursuit by introducing a new class of multi-channel dictionaries, where the atoms are given by a spatial direction and a waveform. The knowledge of the mixing matrix is directly integrated in the decomposition. Compared to the separation by multi-channel Matching Pursuit followed by a clustering, the new algorithm introduces less artifacts whereas the level of residual interferences is about the same. These two methods are compared to Bofill & Zibulevsky's separation algorithm and DUET method. We also study the effect of smoothing the decompositions and the importance of the quality of the estimation of the mixing matrix.
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Communication dans un congrès
Rosca, J. and Erdogmus, D. and Príncipe, J.~C. and Haykin, S. Proc. of the Int'l. Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2006), Mar 2006, Charleston, South Carolina, United States. Springer, 3889, pp.633--640, 2006, LNCS. 〈10.1007/11679363_79〉
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Sylvain Lesage, Sacha Krstulovic, Rémi Gribonval. Under-determined source separation: comparison of two approaches based on sparse decompositions. Rosca, J. and Erdogmus, D. and Príncipe, J.~C. and Haykin, S. Proc. of the Int'l. Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2006), Mar 2006, Charleston, South Carolina, United States. Springer, 3889, pp.633--640, 2006, LNCS. 〈10.1007/11679363_79〉. 〈inria-00544929〉

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