Speech recognition enhancement using beamforming and a genetic algorithm

Chan, Kit Yan; Yiu, Ka Fai; Low, Siow; Nordholm, Sven; Ling, S.

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Access Status

Open access

Authors

Chan, Kit Yan

Yiu, Ka Fai

Low, Siow

Nordholm, Sven

Ling, S.

Date

2009

Collection

Curtin Research Publications

Type

Conference Paper

Metadata

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Abstract

This paper proposes a genetic algorithm (GA) based beamformer to optimize speech recognition accuracy for a pretrained 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.

Citation

Chan, Kit and Yiu, Ka Fai and Low, Siow and Nordholm, Sven and Ling, S. 2009. Speech recognition enhancement using beamforming and a genetic algorithm, in Zhou, W. (ed), 2nd IEEE International Workshop on Data Mining and Artificial Intelligence (DMAI 2009) with Third International Conference on Network and System Security (NSS 2009), Oct 19 2009, pp. 510-515.Gold Coast, Australia: IEEE Computer Society.

Source Title

Proceedings of the 2nd IEEE international workshop on data mining and artificial intelligence (DMAI 2009) with third international conference on network and system security (NSS 2009)

URI

http://hdl.handle.net/20.500.11937/37617

Additional URLs

http://doi.ieeecomputersociety.org/10.1109/NSS.2009.44

Faculty

Curtin Business School

The Digital Ecosystems and Business Intelligence Institute (DEBII)

Department

Digital Ecosystems and Business Intelligence Institute (DEBII)

Remarks

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