Comparison of different techniques on Thai speech recognition

This paper introduces the comparison between Thai isolated word speech recognition techniques using the Hidden Markov Model, the Modified Backpropagation Neural Network, and the Fuzzy-Neural Network. The recognition has been made on the ten isolated Thai numerals from zero to nine under the same sys...

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Bibliographic Details
Published inIEEE. APCCAS 1998. 1998 IEEE Asia-Pacific Conference on Circuits and Systems. Microelectronics and Integrating Systems. Proceedings (Cat. No.98EX242) pp. 177 - 180
Main Authors Ahkuputra, V., Jitapunkul, S., Maneenoi, E., Kasuriya, S., Amornkul, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1998
Subjects
Backpropagation algorithms
Clustering algorithms
Digital signal processing
Hidden Markov models
Multi-layer neural network
Multilayer perceptrons
Natural languages
Neural networks
Speech recognition
Vector quantization
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Summary:This paper introduces the comparison between Thai isolated word speech recognition techniques using the Hidden Markov Model, the Modified Backpropagation Neural Network, and the Fuzzy-Neural Network. The recognition has been made on the ten isolated Thai numerals from zero to nine under the same system configuration for all the approaches. The 15-state left-to-right discrete hidden Markov model in cooperation with the vector quantization technique was compared with the multilayer network using error backpropagation, the modified backpropagation, and also with the fuzzy-neural network with the same configuration. The recognition accuracy using hidden Markov model, neural network, modified neural network and fuzzy-neural network approaches are 84.250 percent, 73.030 percent, 78.000 percent, and 78.300 percent respectively.
ISBN:0780351460
9780780351462
DOI:10.1109/APCCAS.1998.743705