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