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Under-Determined Reverberant Audio Source Separation Using Local Observed Covariance and Auditory-Motivated Time-Frequency Representation
Abstract : We consider the local Gaussian modeling framework for under-determined convolutive audio source separation, where the spatial image of each source is modeled as a zero-mean Gaussian variable with full-rank time- and frequency- dependent covariance. We investigate two methods to improve the accuracy of parameter estimation, based on the use of local observed covariance and auditory-motivated time-frequency representation. We derive an iterative expectation-maximization (EM) algorithm with a suitable initialization scheme. Experimental results over stereo synthetic reverberant mixtures of speech show the effectiveness of the proposed methods.
Cited literature [13 references]
https://hal.inria.fr/inria-00541868
Contributor : Rémi Gribonval <>
Submitted on : Saturday, February 5, 2011 - 1:00:11 PM
Last modification on : Thursday, March 21, 2019 - 2:20:42 PM
Document(s) archivé(s) le : Friday, May 6, 2011 - 2:25:49 AM
Contributor : Rémi Gribonval <>
Submitted on : Saturday, February 5, 2011 - 1:00:11 PM
Last modification on : Thursday, March 21, 2019 - 2:20:42 PM
Document(s) archivé(s) le : Friday, May 6, 2011 - 2:25:49 AM
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2010_LVA_DuongEtAl.pdf
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