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KMID : 0917520040110020217
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Journal of Speech Sciences
2004 Volume.11 No. 2 p.217 ~ p.226
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Machine Scoring Methods Highly-correlated with Human Ratings in Speech Recognizer Detecting Mispronunciation of Foreign Language
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Bae Min-Young
Kwon Chul-Hhong
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Abstract
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An automatic pronunciation correction system provides users with correction guidelines for each pronunciation error. For this purpose, we develop a speech recognition system which automatically classifies pronunciation errors when Koreans speak a foreign language. In this paper, we propose a machine scoring method for automatic assessment of pronunciation quality by the speech recognizer. Scores obtained from an expert human listener are used as the reference to evaluate the different machine scores and to provide targets when training some of algorithms. We use a log-likelihood score and a normalized log-likelihood score as machine scoring methods. Experimental results show that the normalized log-likelihood score had higher correlation with human scores than that obtained using the log-likelihood score.
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KEYWORD
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Automatic detection of mispronunciation, Scoring method
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