Thai phoneme soft segmentation and recognition using hidden Markov models

In this paper, we propose a Thai phoneme recognition system with a soft phoneme segmentation. The soft phoneme segmentation technique is based on the characteristics of Thai language in that the vowel is the core of a syllable. The recognition system utilizes the discrete hidden Markov model to reco...

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Bibliographic Details
Main Authors: Nipon Theera-Umpon, Suppakarn Chansareewittaya, Sansanee Auephanwiriyakul
Format: Conference Proceeding
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=49949105792&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/61053
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Institution: Chiang Mai University
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Summary:In this paper, we propose a Thai phoneme recognition system with a soft phoneme segmentation. The soft phoneme segmentation technique is based on the characteristics of Thai language in that the vowel is the core of a syllable. The recognition system utilizes the discrete hidden Markov model to recognize the Thai phonemes, i.e., 21-class initial consonants, 18-class vowels, and 9-class final consonants. We use the Mel frequency with perceptual linear prediction as the features of a phoneme. We experiment the recognition system on both speaker-dependent and speaker-independent data sets recorded from 30 speakers. The experimental results show promising recognition performances in both cases. ©2007 IEEE.