DocumentCode
1706154
Title
Speech recognition using multilayer perceptron
Author
Ahad, Abdul ; Fayyaz, Ahsan ; Mehmood, Tariq
Volume
1
fYear
2002
Firstpage
103
Abstract
Speech is a very powerful and fast tool for communication. That is the reason why the problem of automatic speech recognition has been fascinating computer scientists. Artificial neural networks (ANN) have been developed to model the functioning of the human brain. They are very powerful classifiers of patterns and hence can be used to recognize speech patterns. This paper discusses the work of our team on the application of ANN to the speech recognition task. We have utilized a particular class of neural networks called multilayer perceptrons (MLP) that utilize the backpropagation of error algorithm for setting of weight. After data acquisition, the speech signal is preprocessed and fed to an MLP for classification. The task is to recognize Urdu digits from zero to nine from a mono-speaker database.
Keywords
backpropagation; multilayer perceptrons; pattern classification; speech processing; speech recognition; ANN; MLP; Urdu digit recognition; artificial neural networks; automatic speech recognition; error backpropagation algorithm; mono-speaker database; multilayer perceptrons; pattern classification; speech signal preprocessing; weight setting; Application software; Artificial neural networks; Automatic speech recognition; Biological neural networks; Brain modeling; Humans; Multilayer perceptrons; Neural networks; Pattern recognition; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Students Conference, 2002. ISCON '02. Proceedings. IEEE
Print_ISBN
0-7803-7505-X
Type
conf
DOI
10.1109/ISCON.2002.1215948
Filename
1215948
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