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dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorSuppakarn Chansareewittayaen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.date.accessioned2018-09-10T04:03:22Z-
dc.date.available2018-09-10T04:03:22Z-
dc.date.issued2007-12-01en_US
dc.identifier.other2-s2.0-49949105792en_US
dc.identifier.other10.1109/IECON.2007.4460136en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=49949105792&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/61053-
dc.description.abstractIn 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.en_US
dc.subjectEngineeringen_US
dc.titleThai phoneme soft segmentation and recognition using hidden Markov modelsen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIECON Proceedings (Industrial Electronics Conference)en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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