NDLI: Under-determined convolutive blind source separation using spatial covariance models

Content Provider	IEEE Xplore Digital Library
Author	Duong, N.Q.K. Vincent, E. Gribonval, R.
Copyright Year	2010
Description	Author affiliation: METISS project team, IRISA-INRIA, Campus de Beaulieu, 35042 Rennes Cedex, France (Duong, N.Q.K.; Vincent, E.; Gribonval, R.)
Abstract	This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency domain as a zero-mean Gaussian random variable whose covariance encodes the spatial properties of the source. We consider two covariance models and address the estimation of their parameters from the recorded mixture by a suitable initialization scheme followed by an iterative expectation-maximization (EM) procedure in each frequency bin. We then align the order of the estimated sources across all frequency bins based on their estimated directions of arrival (DOA). Experimental results over a stereo reverberant speech mixture show the effectiveness of the proposed approach.
Starting Page	9
Ending Page	12
File Size	222757
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5496284
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blind source separation Covariance matrix Frequency estimation Source separation Parameter estimation Direction of arrival estimation Fourier transforms Clustering algorithms Time frequency analysis Random variables permutation problem Convolutive blind source separation under-determined mixtures spatial covariance models EM algorithm
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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