Highly efficient and effective techniques for thai syllable speech recognition

  • Authors:

  • S. Tangwongsan;P. Po-Aramsri;R. Phoophuangpairoj

  • Affiliations:

  • Department of Computer Science, Mahidol University, Bangkok, Thailand;Department of Computer Science, Mahidol University, Bangkok, Thailand;Department of Computer Science, Mahidol University, Bangkok, Thailand

  • Venue:
  • ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
  • Year:
  • 2004

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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.