Presentation 2004/11/30
HMM/ANN System for Vietnamese Continuous Digit Recognition(Additional Presentation)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
DANG NGOC DUC, JOHN-PAUL HOSOM, LUONG CHIMAI, VU TAT THANG,
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Abstract(in English) The study of a system for Vietnamese continuous digit recognition is described. The CSLU Toolkit was used to develop and implement hybrid HMM/ANN recognition systems. Experiments were done with a corpus of 442 sentences with 2340 words, which were extracted from two telephone-speech corpora: "22 Language vl.2" and "Multi-Language Telephone Speech vl.2". In our experiments, a context-dependent phoneme recognizer has achieved better recognition performance than a context-dependent demi-syllable recognizer and a context-independent phoneme recognizer. Among feature sets applied to the context-dependent phoneme recognizer, the set of 12 PLP features with CMS, energy and corresponding delta values has achieved the best recognition result (96.83% word accuracy and 87.67% sentence correct).
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Paper # AI2004-62
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Committee AI
Conference Date 2004/11/30(1days)
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Language ENG
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Title (in English) HMM/ANN System for Vietnamese Continuous Digit Recognition(Additional Presentation)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
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1st Author's Name DANG NGOC DUC
1st Author's Affiliation Alcatel NSV, Vietnam Post and Telecommunication.()
2nd Author's Name JOHN-PAUL HOSOM
2nd Author's Affiliation Alcatel NSV, Vietnam Post and Telecommunication.
3rd Author's Name LUONG CHIMAI
3rd Author's Affiliation Center for Spoken Language Understanding (CSLU-OGI)
4th Author's Name VU TAT THANG
4th Author's Affiliation Institute of Information Technology, Vietnamese Academy of Science and Technology
Date 2004/11/30
Paper # AI2004-62
Volume (vol) vol.104
Number (no) 488
Page pp.pp.-
#Pages 4
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