Speech recognition enhancement using beamforming and a genetic algorithm

Chan, KY; Low, SY; Nordholm, S; Yiu, KFC; Ling, SH

Speech recognition enhancement using beamforming and a genetic algorithm

Chan, KY Low, SY Nordholm, S Yiu, KFC Ling, SH

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Publication Type:: Conference Proceeding
Citation:: NSS 2009 - Network and System Security, 2009, pp. 510 - 515
Issue Date:: 2009-12-01

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Field	Value	Language
dc.contributor.author	Chan, KY	en_US
dc.contributor.author	Low, SY	en_US
dc.contributor.author	Nordholm, S	en_US
dc.contributor.author	Yiu, KFC	en_US
dc.contributor.author	Ling, SH https://orcid.org/0000-0003-0849-5098	en_US
dc.date.issued	2009-12-01	en_US
dc.identifier.citation	NSS 2009 - Network and System Security, 2009, pp. 510 - 515	en_US
dc.identifier.isbn	9780769538389	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11110
dc.description.abstract	This paper proposes a genetic algorithm (GA) based beamformer to optimize speech recognition accuracy for a pre-trained speech recognizer. The proposed beamformer is designed to tackle the non-differentiable and non-linear natures of speech recognition by employing the GA algorithm to search for the optimal beamformer weights. Specifically, a population of beamformer weights is reproduced by crossover and mutation until the optimal beamformer weights are obtained. Results show that the speech recognition accuracies can be greatly improved even in noisy environments. © 2009 IEEE.	en_US
dc.relation.ispartof	NSS 2009 - Network and System Security	en_US
dc.relation.isbasedon	10.1109/NSS.2009.44	en_US
dc.title	Speech recognition enhancement using beamforming and a genetic algorithm	en_US
dc.type	Conference Proceeding
utslib.for	090602 Control Systems, Robotics and Automation	en_US
dc.location.activity	Gold Coast, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper proposes a genetic algorithm (GA) based beamformer to optimize speech recognition accuracy for a pre-trained speech recognizer. The proposed beamformer is designed to tackle the non-differentiable and non-linear natures of speech recognition by employing the GA algorithm to search for the optimal beamformer weights. Specifically, a population of beamformer weights is reproduced by crossover and mutation until the optimal beamformer weights are obtained. Results show that the speech recognition accuracies can be greatly improved even in noisy environments. © 2009 IEEE.

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http://hdl.handle.net/10453/11110