Please use this identifier to cite or link to this item:
Title: Phoneme and tonal accent recognition for Thai speech
Authors: Nipon Theera-Umpon
Suppakarn Chansareewittaya
Sansanee Auephanwiriyakul
Keywords: Computer Science
Issue Date: 15-Sep-2011
Abstract: 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.
ISSN: 09574174
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.

Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.