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Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation

Matthieu Kowalski 1 Emmanuel Vincent 2 Rémi Gribonval 2
2 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We consider the problem of extracting the source signals from an under-determined convolutive mixture assuming known mixing filters. State-of-the-art methods operate in the time-frequency domain and rely on narrowband approximation of the convolutive mixing process by complex-valued multiplication in each frequency bin. The source signals are then estimated by minimizing either a mixture fitting cost or a l1 source sparsity cost, under possible constraints on the number of active sources. In this article, we define a wideband l2 mixture fitting cost circumventing the above approximation and investigate the use of a l12 mixed-norm cost promoting disjointness of the source timefrequency representations. We design a family of convex functionals combining these costs and derive suitable optimization algorithms. Experiments indicate that the proposed wideband methods result in a signal-to-distortion ratio improvement of 2 to 5 dB compared to the state-of-the-art on reverberant speech mixtures.
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https://hal.archives-ouvertes.fr/hal-00435897
Contributor : Matthieu Kowalski <>
Submitted on : Wednesday, November 25, 2009 - 11:31:31 AM
Last modification on : Friday, December 20, 2019 - 11:48:02 AM
Document(s) archivé(s) le : Tuesday, October 16, 2012 - 2:50:38 PM

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Matthieu Kowalski, Emmanuel Vincent, Rémi Gribonval. Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation. IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2010, 18 (7), pp.1818 - 1829. ⟨10.1109/TASL.2010.2050089⟩. ⟨hal-00435897v1⟩

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