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Beamspace blind signal separation for speech enhancement

Beamspace blind signal separation for speech enhancement
Beamspace blind signal separation for speech enhancement
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.
1389-4420
313-330
Low, S.Y.
8fd903a4-b0b0-4c1c-9cc7-c2fe87109376
Yiu, K.F.C.
b47e9abf-e3f9-4096-b428-6747c552997e
Nordholm, S.
d2441721-2cf0-4387-a95d-7cd2b956c014
Low, S.Y.
8fd903a4-b0b0-4c1c-9cc7-c2fe87109376
Yiu, K.F.C.
b47e9abf-e3f9-4096-b428-6747c552997e
Nordholm, S.
d2441721-2cf0-4387-a95d-7cd2b956c014

Low, S.Y., Yiu, K.F.C. and Nordholm, S. (2009) Beamspace blind signal separation for speech enhancement. Optimization and Engineering, 10 (2), 313-330. (doi:10.1007/s11081-008-9060-4).

Record type: Article

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.

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Published date: 1 June 2009
Organisations: Southampton Wireless Group

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Local EPrints ID: 369129
URI: https://eprints.soton.ac.uk/id/eprint/369129
ISSN: 1389-4420
PURE UUID: a02860e9-96d9-4772-b389-b37a159f4205

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Date deposited: 25 Sep 2014 12:06
Last modified: 18 Jul 2017 01:40

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Contributors

Author: S.Y. Low
Author: K.F.C. Yiu
Author: S. Nordholm

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