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Development of a speaker recognition system using wavelets and artificial neural networks
conference contribution
posted on 2001-01-01, 00:00 authored by S Woo, Chee Peng LimChee Peng Lim, R OsmanThis paper addresses the problem of speaker recognition from speech signals. The study focuses on the development of a speaker recognition system comprising two modules: a wavelet-based feature extractor, and a neural-network-based classifier. We have conducted a number of experiments to investigate the applicability of Discrete Wavelet Transform (D WT) in extracting discriminative features from the speech signals, and have examined various models from the Adaptive Resonance Theory (ART) family of neural networks in classijjing the extracted features. The results indicate that DWT could be a potential feature extraction tool for speaker recognition. In addition, the ART-based classijiers have yielded very promising recognition accuracy at more than 81%.
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Event
International Symposium on Intelligent Multimedia, Video and Speech Processing (1st : 2001 : Hong Kong, China)Pagination
413 - 416Publisher
IEEELocation
Hong KongPlace of publication
Piscataway, N. J.Start date
2001-05-02End date
2001-05-04Language
engPublication classification
E1.1 Full written paper - refereedTitle of proceedings
ISIMP 2001 : Proceedings of the 2001 IEEE International Symposium on Intelligent Multimedia, Video and Speech ProcessingUsage metrics
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