Thesis (Ph.D.)--Chulalongkorn University, 2003

The objective of this dissertation is to develop a new speech unit on acoustic modeling of the Thai language. The Thai syllables were studied in both acoustical and phonological properties. From the acoustical point of view, in the syllable structure, the final consonant is strongly influenced by the vowel duration. This relationship occurs only between the vowel and the final consonant. In contrase, the initial consonant is not affected by the duration of the vowel. Hence, the vowel and the final consonant are tightly tied while an inital consonant is loosely tied with the vowel in the syllable. From a phonological point of view, a syllable is composed of a pair of an onset and a rhyme unit. The onset consists of an initial consonant and its transition towards the following vowel. Along with the onset, the rhyme is composed of a vowel, a final consonant, and a tone. The onset-rhyme not only includes its contextual information, but also embeds the language modeling at the syllable level. Consequently, the decomposition of the syllable into an onset and rhyme is appropriate to the Thai language. The whole set of Thai syllables can be recognized by identifying onsets and rhymes. This research has objective to compare the efficiency of the units. Therefore a tone recognition system is not implemented in this research. To evaluate the effectiveness of the proposed acoustic model, various conventional speech units used in speech recognition systems have been investigated. Several experiments have been carried out to find the proper speech unit that can accurately create acoustic model and give a higher recognition rate. Results of recognition rates under different acoustic models are given and compared. The speech corpus used for training in this experiment was recorded from 9 male and 11 female speakers. This group of speakers also produced the speaker-dependent test set. In addition, the speaker-independent test set was produced from other 5 male and 5 female speakers. This speech corpus was designed to cover all onset-rhyme units in the Thai language. Experimental results show that the onset-rhyme model improves on the efficiency of other speech units. The onset-rhyme model improves on the accuracy of the baseline monophone model, the inter-syllable triphone model, and the context-dependent Initial-Final model by nearly 26.2%, 6.4%, and 4.2% for the speaker-dependent systems using only an acoustic model, and 29.7%, 6.0%, and 4.2% for the speaker-dependent systems using both acoustic and language model respectively. Using the language model, the onset accuracy is increased by around 16-21% for both SD and SI systems. In addition, the accuracy of the rhyme is substantially improved by nearly 45-47% for the SD and SI systems when the language model is applied. The results show that the onset-rhyme models attain a high recognition rate. Moreover, they also give more efficiency in terms of system complexity.