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Variational EM for Binaural Sound-Source Separation and Localization
Abstract : The sound-source separation and localization (SSL) problems are addressed within a unified formulation. Firstly, a mapping between white-noise source locations and binaural cues is estimated. Secondly, SSL is solved via Bayesian inversion of this mapping in the presence of multiple sparse-spectrum emitters (such as speech), noise and reverberations. We propose a variational EM algorithm which is described in detail together with initialization and convergence issues. Extensive real-data experiments show that the method outperforms the state-of-the-art both in separation and localization (azimuth and elevation).
Cited literature [20 references]
https://hal.inria.fr/hal-00823453
Contributor : Florence Forbes <>
Submitted on : Friday, May 17, 2013 - 8:56:33 AM
Last modification on : Friday, July 3, 2020 - 9:45:34 AM
Document(s) archivé(s) le : Sunday, August 18, 2013 - 4:13:27 AM
Contributor : Florence Forbes <>
Submitted on : Friday, May 17, 2013 - 8:56:33 AM
Last modification on : Friday, July 3, 2020 - 9:45:34 AM
Document(s) archivé(s) le : Sunday, August 18, 2013 - 4:13:27 AM
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deleforge_icassp_rev.pdf
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