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Adaptation of source-specific dictionaries in Non-Negative Matrix Factorization for source separation

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4 Author(s)
Jaureguiberry, X. ; Audionamix, Paris, France ; Leveau, P. ; Maller, S. ; Burred, J.J.

This paper concerns the adaptation of spectrum dictionaries in audio source separation with supervised learning. Supposing that samples of the audio sources to separate are available, a filter adaptation in the frequency domain is proposed in the context of Non-Negative Matrix Factorization with the Itakura-Saito divergence. The algorithm is able to retrieve the acoustical filter applied to the sources with a good accuracy, and demonstrates significantly higher performances on separation tasks when compared with the non-adaptive model.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on

Date of Conference:

22-27 May 2011