NDLI: The speech recognition system for all the Chinese syllables using hidden Markov model

Content Provider	IEEE Xplore Digital Library
Author	Yu Qing Gao Yong Bin Chen Tai Yi Huang
Copyright Year	1990
Description	Author affiliation: Nat. Lab of Pattern Recognition, Chinese Acad. of Sci., Beijing, China (Yu Qing Gao)
Abstract	A speech recognition system for all the Chinese syllables is described. The system is a hidden Markov model (HMM)-based recognizer using the initial consonant and the final vowel as the recognition unit with various features derived from linear predictive coding cepstral coefficients. In order to deal with the difficulties introduced by variabilities of speech, the authors transformed a cepstral for a vowel and a multimodel for a consonant. Each element is represented by a hidden Markov model. It is shown that the HMM alone is inadequate in such a difficult task. A syllable recognition accuracy of 93% for a speaker-dependent test is reported. The feasibility of the system is shown.
Starting Page	240
Ending Page	242
File Size	298972
Page Count	3
File Format	PDF
ISBN	0818620625
DOI	10.1109/ICPR.1990.119362
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-06-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech recognition Hidden Markov models Covariance matrix Acoustic scattering Cepstral analysis Vocabulary Testing Pattern recognition Automation Linear predictive coding
Content Type	Text
Resource Type	Article

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The speech recognition system for all the Chinese syllables using hidden Markov model