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Communication Dans Un Congrès Année : 2003

Non negative sparse representation for Wiener based source separation with a single sensor

Résumé

We propose a new method to perform the separation of two sound sources from a single sensor. This method generalizes the Wiener filtering with locally stationary, non gaussian, parametric source models. The method involves a learning phase for which we propose three different algorithm. In the separation phase, we use a sparse non negative decomposi- tion algorithm of our own. The algorithms are evaluated on the separation of real audio data.
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Dates et versions

inria-00574784 , version 1 (08-03-2011)

Identifiants

Citer

Laurent Benaroya, Lorcan Mcdonagh, Frédéric Bimbot, Rémi Gribonval. Non negative sparse representation for Wiener based source separation with a single sensor. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2003), Apr 2003, Hong-Kong, Hong Kong SAR China. pp.VI/613--VI/616, ⟨10.1109/ICASSP.2003.1201756⟩. ⟨inria-00574784⟩
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