Informed Source Separation Using Latent Components

Abstract : We address the issue of source separation in a particular informed configuration where both the sources and the mixtures are assumed to be known during a so-called encoding stage. This knowledge enables the computation of a side information which ought to be small enough to be watermarked in the mixtures. At the decoding stage, the sources are no longer assumed to be known, only the mixtures and the side information are processed to perform source separation. The proposed method models the sources jointly using latent variables in a framework close to multichannel nonnegative matrix factorization and models the mixing process as linear filtering. Separation at the decoding stage is done using generalized Wiener filtering of the mixtures. An experimental setup shows that the method gives very satisfying results with mixtures composed of many sources. A study of its performance with respect to the number of latent variables is presented.
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Communication dans un congrès
Vincent Vigneron and Vicente Zarzoso and Eric Moreau and Rémi Gribonval and Emmanuel Vincent. Latent Variable Analysis and Signal Separation, 2010, Saint Malo, France. Springer, 6365, pp.498--505, 2010, Lecture Notes in Computer Science. 〈http://link.springer.com/chapter/10.1007%2F978-3-642-15995-4_62〉. 〈10.1007/978-3-642-15995-4_62〉
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https://hal.inria.fr/hal-00945298
Contributeur : Antoine Liutkus <>
Soumis le : mercredi 12 février 2014 - 10:05:59
Dernière modification le : mercredi 21 février 2018 - 07:50:09

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Antoine Liutkus, Roland Badeau, Gaël Richard. Informed Source Separation Using Latent Components. Vincent Vigneron and Vicente Zarzoso and Eric Moreau and Rémi Gribonval and Emmanuel Vincent. Latent Variable Analysis and Signal Separation, 2010, Saint Malo, France. Springer, 6365, pp.498--505, 2010, Lecture Notes in Computer Science. 〈http://link.springer.com/chapter/10.1007%2F978-3-642-15995-4_62〉. 〈10.1007/978-3-642-15995-4_62〉. 〈hal-00945298〉

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