Abstract
This paper presents Thai monophthongal vowels recognition. The Thai monophthongs were qualitatively recognized by the 3-state left-to-right continuous density hidden Markov model. The 18 monophthongs are qualitatively 9 different vowels, each of which has two members, short and long. The LPC cepstral coefficients were used and the temporal cepstral derivative was additionally utilized to compare efficiency of the additional feature with the single feature. Qualitative recognition means that short and long vowel pairs were categorized in the same model. Thai polysyllabic words were used in this research. The database consists of 2100 training phonemes from 30 speakers and 1378 testing phonemes from a different group of 20 speakers, respectively. The highest recognition rate of the single feature obtained from 18-order LPC cepstral coefficients is 86.983 percent, while the recognition rate of the 16-order LPC cepstral coefficients plus temporal derivative is 94.580 percent. The results indicate that all the LPC cepstral coefficients associated with temporal derivative have better recognition accuracy than those of LPC cepstral coefficients. It is concluded that the additional temporal derivative can improve recognition rate. The misclassification is analyzed and it is concluded that this resulted from excessively overlapped distributions of vowels in the low- and back vowel groups, respectively.
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