Thai phoneme soft segmentation and recognition using hidden Markov models

• Main Authors: Theera-Umpon N., Chansareewittaya S., Auephanwiriyakul S.
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Online Access: http://www.scopus.com/inward/record.url?eid=2-s2.0-49949105792&partnerID=40&md5=996dcd9d7cc7d0f8ea7b44cbe7d8eed2; http://cmuir.cmu.ac.th/handle/6653943832/1313
• 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.