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Speech Recognition of Multi-Syllable Words Using Soft Computing Techniques  

Lee, Jong-Soo (연세대학교 기계공학부)
Yoon, Ji-Won (연세대학교 대학원 기계공학과)
Publication Information
Transactions of the Society of Information Storage Systems / v.6, no.1, 2010 , pp. 18-24 More about this Journal
Abstract
The performance of the speech recognition mainly depends on uncertain factors such as speaker's conditions and environmental effects. The present study deals with the speech recognition of a number of multi-syllable isolated Korean words using soft computing techniques such as back-propagation neural network, fuzzy inference system, and fuzzy neural network. Feature patterns for the speech recognition are analyzed with 12th order thirty frames that are normalized by the linear predictive coding and Cepstrums. Using four models of speech recognizer, actual experiments for both single-speakers and multiple-speakers are conducted. Through this study, the recognizers of combined fuzzy logic and back-propagation neural network and fuzzy neural network show the better performance in identifying the speech recognition.
Keywords
Speech Recognition Algorithm; Neural Network; Fuzzy Logic; Fuzzy Neural Network; Multi-Syllable Word;
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