Publication: Highly efficient and effective techniques for Thai syllable speech recognition
Issued Date
2004-12-01
Resource Type
ISSN
16113349
03029743
03029743
Other identifier(s)
2-s2.0-35048825303
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Mahidol University
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SCOPUS
Bibliographic Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.3321, (2004), 259-270
Suggested Citation
S. Tangwongsan, P. Po-Aramsri, R. Phoophuangpairoj Highly efficient and effective techniques for Thai syllable speech recognition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.3321, (2004), 259-270. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/21286
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Title
Highly efficient and effective techniques for Thai syllable speech recognition
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Abstract
This paper presents a Thai syllable speech recognition system with the capability to achieve high accuracy of Thai syllable speech and Thai tone recognition. The recognition accuracy of 97.84% is achieved for Thai syllable speech recognition using the Continuous Density Hidden Markov Model (CDHMM). To provide a faster response, a beam pruning technique is applied, in which the result shows that by using this technique with an appropriate beam width, the recognition time can be reduced by more than 4 times. As Thai is tonal language, tone recognition is crucial for distinguishing meanings of Thai syllables. To obtain high rates of tone recognition in the Thai language, the CDHMM and a mixed acoustic feature method are employed. The tone recognition rates of 97.88%, 97.36%, 98.81%, 90.67% and 100.0% are achieved for mid, low, falling, high and rising tones, respectively. © Springer-Verlag Berlin Heidelberg 2004.