Beamspace blind signal separation for speech enhancement |
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Authors: | Siow Yong Low Ka-Fai Cedric Yiu Sven Nordholm |
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Affiliation: | (1) Western Australian Telecommunications Research Institute, Crawley, WA, 6009, Australia;(2) Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, People’s Republic of China |
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Abstract: | Signal processing methods for speech enhancement are of vital interest for communications equipments. In particular, multichannel
algorithms, which perform spatial filtering to separate signals that have overlapping frequency content but different spatial
origins, are important for a wide range of applications. Two of the most popular multichannel methods are blind signal separation
(BSS) and beamforming. Briefly, (BSS) separates mixed sources by optimizing the statistical independence among the outputs
whilst beamforming optimizes the look direction of the desired source(s). However, both methods have separation limitations,
in that BSS succumbs to reverberant environments and beamforming is very sensitive to array model mismatch. In this paper,
we propose a novel hybrid scheme, called beamspace BSS, which is intended to compensate the aforementioned separation weaknesses
by jointly optimizing the spatial selectivity and statistical independence of the sources. We show that beamspace BSS outperforms
the separation performance of the conventional sensor space BSS significantly, particularly in reverberant room environments.
K.F.C. Yiu is supported by RGC Grant PolyU. 7191/06E and the research committee of the Hong Kong Polytechnic University. |
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Keywords: | Blind signal separation Beamspace Speech enhancement Microphone arrays |
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