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Text-dependent speaker recognition using the Fuzzy ARTMAP neural network
conference contribution
posted on 2000-01-01, 00:00 authored by S Woo, Chee Peng LimChee Peng Lim, R OsmanSpeaker recognition is the process of automatically recognizing the speaker by analyzing individual information contained in the speech waves. In this paper, we discuss the development of an intelligent system for text-dependent speaker recognition. The system comprises two main modules, a wavelet-based signal-processing module for feature extraction of speech waves, and an artificial-neural-network-based classifier module to identify and categorize the speakers. Wavelet is used in de-noising and in compressing the speech signals. The wavelet family that we used is the Daubechies Wavelets. After extracting the necessary features from the speech waves, the features were then fed to a neural-network-based classifier to identify the speakers. We have implemented the Fuzzy ARTMAP (FAM) network in the classifier module to categorize the de-noised and compressed signals. The proposed intelligent learning system has been applied to a case study of text-dependent speaker recognition problem.
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Event
Trends in Electronics Conference (2000 : Kuala Lumpur, Malaysia)Publisher
IEEELocation
Kuala Lumpur, MalaysiaPlace of publication
Piscataway, N. J.Publisher DOI
Start date
2000-09-24End date
2000-09-27ISBN-10
0780363558Language
engPublication classification
E1.1 Full written paper - refereedTitle of proceedings
TENCON 2000 : Proceedings : Intelligent systems and technologies for the new millenniumUsage metrics
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