Thai phoneme soft segmentation and recognition using hidden Markov models

• Main Authors: Nipon Theera-Umpon, Suppakarn Chansareewittaya, Sansanee Auephanwiriyakul
• Format: Conference Proceeding
• Published: 2018
• Subjects: Engineering
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=49949105792&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/61053
• Institution: Chiang Mai University

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.