Presentation 1996/7/26
HMM based phoneme classification using several types of segmentation algorithms
S.K. Podder, S. Tazaki, S. Tsuzuki, Y. Yamada,
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Abstract(in English) We have attempted to automatically classify the Japanese 23 phonemes (extracted from the isolated mono-syllables) hierarchically by using Hidden Markov models (HMM). For extracting the phonemes we have considered four different types of segmentation algorithms, viz., MDS, MMDS, MLS, and LB. Additionally we have imposed some kind of linear weighting on the discrete probability density function of HMM. The results show that classification efficiency is comparatively better for MMDS and weighting improves the efficiency by 21% for the training data and by 8.5% for the testing data.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) MDS(Minimal distortion segmentation) / MMDS(modified MDS) / MLS(Maximum likelihood segmentation) / LB(Level building) / VQ(Vector quantization)
Paper # IT96-32
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Committee IT
Conference Date 1996/7/26(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) HMM based phoneme classification using several types of segmentation algorithms
Sub Title (in English)
Keyword(1) MDS(Minimal distortion segmentation)
Keyword(2) MMDS(modified MDS)
Keyword(3) MLS(Maximum likelihood segmentation)
Keyword(4) LB(Level building)
Keyword(5) VQ(Vector quantization)
1st Author's Name S.K. Podder
1st Author's Affiliation Ehime University, Faculty of Engineering, Department of Electrical and Electronics Engineering()
2nd Author's Name S. Tazaki
2nd Author's Affiliation Ehime University, Faculty of Engineering, Department of Electrical and Electronics Engineering
3rd Author's Name S. Tsuzuki
3rd Author's Affiliation Ehime University, Faculty of Engineering, Department of Electrical and Electronics Engineering
4th Author's Name Y. Yamada
4th Author's Affiliation Ehime University, Faculty of Engineering, Department of Electrical and Electronics Engineering
Date 1996/7/26
Paper # IT96-32
Volume (vol) vol.96
Number (no) 203
Page pp.pp.-
#Pages 6
Date of Issue