> Problem statement: To implementation of the Hidden Markov Model (HMM)-based Thai speech synthesis system, it is necessary to understand the phonology system for a language. Without the phonological information, the contextual factors of tree-based context clustering cannot be completed. Approach: The existing speech units in Thai are studied thoroughly so that the synthesis system can provide all of them in an appropriate way. In the study of speech in a specific language, we have to categorize the speech into sounds. Then summarize them in some specific ways including its function, how it appears in speech, the relation with other sounds and also how it contributes to syllable or word. Results: The speech units of the phoneme, syllable, word, phrase and sentence level are studied and explained, respectively. Conclusion: The important information of Thai phonology system has been summarized. It is expected to apply them efficiently in the HMM-based Thai speech synthesis system.
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