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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Tangwongsan, S., Po-Aramsri, P., Phoophuangpairoj, R. (2004). Highly Efficient and Effective Techniques for Thai Syllable Speech Recognition. In: Maher, M.J. (eds) Advances in Computer Science - ASIAN 2004. Higher-Level Decision Making. ASIAN 2004. Lecture Notes in Computer Science, vol 3321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30502-6_19
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DOI: https://doi.org/10.1007/978-3-540-30502-6_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24087-7
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