Automatic voice recognition using artificial neural network approach

Author

Botros, N. ; Deiri, M.Z. ; Hsu, P.

Author_Institution

Dept. of Electr. Eng., Southern Illinois Univ., Carbondale, IL, USA

fYear

1989

fDate

14-16 Aug 1989

Firstpage

763

Abstract

Research to develop an algorithm for isolated-word recognition is described. Features extraction is carried out by applying a linear predictive coding (LPC) algorithm with order of 10. To implement and test the proposed algorithm a microcomputer-based data acquisition system has been designed and constructed. To examine the similarity between the reference and the training sets, a back propagation artificial neural net model with three layers is implemented. The adaptation rule implemented in this network is the generalized least mean square (LMS) rule

Keywords

encoding; filtering and prediction theory; learning systems; neural nets; speech recognition; adaptation rule; artificial neural network approach; back propagation artificial neural net model; feature extraction; generalized least mean square; isolated-word recognition; linear predictive coding; microcomputer-based data acquisition system; training sets; Algorithm design and analysis; Artificial neural networks; Automatic speech recognition; Equations; Feature extraction; Linear predictive coding; Prediction algorithms; Signal processing algorithms; Speech analysis; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1989., Proceedings of the 32nd Midwest Symposium on

Conference_Location

Champaign, IL

Type

conf

DOI

10.1109/MWSCAS.1989.101967

Filename

101967