DocumentCode :
2523216
Title :
Using Genetic Algorithm to Improve the Performance of Speech Recognition Based on Artificial Neural Network
Author :
Lan, Min-Lun ; Pan, Shing-Tai ; Lai, Chih-Chin
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Shu-Te Univ.
Volume :
2
fYear :
2006
fDate :
Aug. 30 2006-Sept. 1 2006
Firstpage :
527
Lastpage :
530
Abstract :
The goal of this paper is to apply artificial neural network (ANN) to recognize speech. We use genetic algorithm (GA) to replace the steepest descent method (SDM) for the training of BPNN such that a global search of optimal weight in neural network can be. Thus, the performance of speech recognition was improved by the proposed method in this paper. The non-specific speaker recognition, which is trained by SDM, the recognition rate achieve up to 91% in this experiment. This paper shows that if BPNN is trained by genetic algorithm, higher recognition rate is attained
Keywords :
backpropagation; genetic algorithms; neural nets; speech recognition; BPNN; artificial neural network; backpropagation; genetic algorithm; speech recognition; steepest descent method; Artificial neural networks; Computer science; Genetic algorithms; Hidden Markov models; Neural networks; Signal detection; Speaker recognition; Speech processing; Speech recognition; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
Type :
conf
DOI :
10.1109/ICICIC.2006.372
Filename :
1692041
Link To Document :
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