Title :
Speech Recognition Enhancement Using Beamforming and a Genetic Algorithm
Author :
Chan, K.Y. ; Low, S.Y. ; Nordholm, S. ; Yiu, K.F.C. ; Ling, S.H.
Author_Institution :
Digital Ecosyst. & Bus. Intell. Inst., Curtin Univ. of Technol., Perth, WA, Australia
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.
Keywords :
array signal processing; genetic algorithms; speech enhancement; speech recognition; beamforming; genetic algorithm; optimal beamformer weight; pretrained speech recognizer; speech recognition enhancement; Acoustic noise; Array signal processing; Australia; Genetic algorithms; Hidden Markov models; Microphones; Nonlinear distortion; Signal processing; Speech recognition; Working environment noise; Speech recognition; beamforming; genetic algorithm; signal enhancement;
Conference_Titel :
Network and System Security, 2009. NSS '09. Third International Conference on
Conference_Location :
Gold Coast, QLD
Print_ISBN :
978-1-4244-5087-9
Electronic_ISBN :
978-0-7695-3838-9
DOI :
10.1109/NSS.2009.44