A Sparsity-Based Method to Solve Permutation Indeterminacy in Frequency-Domain Convolutive Blind Source Separation

Authors:
Prasad Sudhakar;Rémi Gribonval
Affiliations:
METISS Team, Centre Recherche INRIA Rennes - Bretagne Atlantique, Rennes cedex, France 35042;METISS Team, Centre Recherche INRIA Rennes - Bretagne Atlantique, Rennes cedex, France 35042
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Blind Source Separation of Convolutive Mixtures of Speech in Frequency Domain

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

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Abstract

Existing methods for frequency-domain estimation of mixing filters in convolutive blind source separation (BSS) suffer from permutation and scaling indeterminacies in sub-bands. However, if the filters are assumed to be sparse in the time domain, it is shown in this paper that the ***1 -norm of the filter matrix increases as the sub-band coefficients are permuted. With this motivation, an algorithm is then presented which solves the source permutation indeterminacy, provided there is no scaling indeterminacy in sub-bands. The robustness of the algorithm to noise is also presented.