Phoneme and tonal accent recognition for Thai speech

In this paper, we investigate the application of a phoneme recognition system with a soft phoneme segmentation procedure for Thai speech. In addition, we propose a new method to classify the tonal accent of a syllable. The recognition system classifies Thai phonemes, including the 21-class initial c...

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Main Authors: Nipon Theera-Umpon, Suppakarn Chansareewittaya, Sansanee Auephanwiriyakul
Format: Journal
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/49870
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-498702018-09-04T04:20:46Z Phoneme and tonal accent recognition for Thai speech Nipon Theera-Umpon Suppakarn Chansareewittaya Sansanee Auephanwiriyakul Computer Science Engineering In this paper, we investigate the application of a phoneme recognition system with a soft phoneme segmentation procedure for Thai speech. In addition, we propose a new method to classify the tonal accent of a syllable. The recognition system classifies Thai phonemes, including the 21-class initial consonants, the 18-class vowels, and the 9-class final consonants, using discrete hidden Markov models. Two features, i.e., the Mel frequency with perceptual linear prediction and the Mel frequency cepstrum coefficients, are compared to investigate their utilities in phoneme recognition. Neural networks are applied to classify the 5-class tonal accents by using the temporal variation of pitch frequencies across syllables as features. Speaker-dependent and speaker-independent data sets recorded from 30 speakers are used to test our recognition system. The experimental results show promising recognition performances for the phonemes and tonal accents in both data sets. © 2010 Elsevier Ltd. All rights reserved. 2018-09-04T04:19:34Z 2018-09-04T04:19:34Z 2011-09-15 Journal 09574174 2-s2.0-79957996410 10.1016/j.eswa.2011.04.142 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79957996410&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/49870
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Engineering
spellingShingle Computer Science
Engineering
Nipon Theera-Umpon
Suppakarn Chansareewittaya
Sansanee Auephanwiriyakul
Phoneme and tonal accent recognition for Thai speech
description In this paper, we investigate the application of a phoneme recognition system with a soft phoneme segmentation procedure for Thai speech. In addition, we propose a new method to classify the tonal accent of a syllable. The recognition system classifies Thai phonemes, including the 21-class initial consonants, the 18-class vowels, and the 9-class final consonants, using discrete hidden Markov models. Two features, i.e., the Mel frequency with perceptual linear prediction and the Mel frequency cepstrum coefficients, are compared to investigate their utilities in phoneme recognition. Neural networks are applied to classify the 5-class tonal accents by using the temporal variation of pitch frequencies across syllables as features. Speaker-dependent and speaker-independent data sets recorded from 30 speakers are used to test our recognition system. The experimental results show promising recognition performances for the phonemes and tonal accents in both data sets. © 2010 Elsevier Ltd. All rights reserved.
format Journal
author Nipon Theera-Umpon
Suppakarn Chansareewittaya
Sansanee Auephanwiriyakul
author_facet Nipon Theera-Umpon
Suppakarn Chansareewittaya
Sansanee Auephanwiriyakul
author_sort Nipon Theera-Umpon
title Phoneme and tonal accent recognition for Thai speech
title_short Phoneme and tonal accent recognition for Thai speech
title_full Phoneme and tonal accent recognition for Thai speech
title_fullStr Phoneme and tonal accent recognition for Thai speech
title_full_unstemmed Phoneme and tonal accent recognition for Thai speech
title_sort phoneme and tonal accent recognition for thai speech
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79957996410&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/49870
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