Speech recognition enhancement using beamforming and a genetic algorithm
| dc.contributor.author | Chan, Kit Yan | |
| dc.contributor.author | Yiu, Ka Fai | |
| dc.contributor.author | Low, Siow | |
| dc.contributor.author | Nordholm, Sven | |
| dc.contributor.author | Ling, S. | |
| dc.contributor.editor | Wanlei Zhou | |
| dc.date.accessioned | 2017-01-30T14:04:47Z | |
| dc.date.available | 2017-01-30T14:04:47Z | |
| dc.date.created | 2010-03-29T20:04:20Z | |
| dc.date.issued | 2009 | |
| dc.identifier.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. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/37617 | |
| dc.description.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. | |
| dc.publisher | IEEE Computer Society | |
| dc.relation.uri | http://doi.ieeecomputersociety.org/10.1109/NSS.2009.44 | |
| dc.subject | beamforming | |
| dc.subject | genetic algorithm | |
| dc.subject | Speech recognition | |
| dc.subject | signal enhancement | |
| dc.title | Speech recognition enhancement using beamforming and a genetic algorithm | |
| dc.type | Conference Paper | |
| dcterms.source.startPage | 510 | |
| dcterms.source.endPage | 515 | |
| dcterms.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) | |
| dcterms.source.series | 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) | |
| dcterms.source.isbn | 9780769538389 | |
| dcterms.source.conference | 2nd IEEE International Workshop on Data Mining and Artificial Intelligence (DMAI 2009) with Third International Conference on Network and System Security (NSS 2009) | |
| dcterms.source.conference-start-date | Oct 19 2009 | |
| dcterms.source.conferencelocation | Gold Coast, Australia | |
| dcterms.source.place | Australia | |
| curtin.note |
Copyright © 2009 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| curtin.department | Digital Ecosystems and Business Intelligence Institute (DEBII) | |
| curtin.accessStatus | Open access | |
| curtin.faculty | Curtin Business School | |
| curtin.faculty | The Digital Ecosystems and Business Intelligence Institute (DEBII) |