S. TangwongsanP. Po-AramsriR. PhoophuangpairojMahidol University2018-07-242018-07-242004-12-01Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.3321, (2004), 259-27016113349030297432-s2.0-35048825303https://repository.li.mahidol.ac.th/handle/20.500.14594/21286This 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.Mahidol UniversityComputer ScienceMathematicsArticleSCOPUS