Presentation 2005/9/10
Construction of a Corpus for HMM-based Continuous Manual Alphabet Recognition and Synthesis
Yuta EMOTO, Chiyomi MIYAJIMA, Katsunobu ITOU, Kazuya TAKEDA,
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Abstract(in English) We construct an alphabetically-balanced word corpus for hidden Markov model (HMM)-based continuous Japanese manual alphabet recognition and animation synthesis. HMM-based continuous manual alphabet word recognition experiments are carried out using training and test data sets collected with a data glove and a position sensor according to the text of the word corpus. A high word recognition rate of 97.9% is obtained in a 15k-word large-vocabulary word recognition task. Furthermore. HMM-based continuous manual alphabet animation synthesis conducted by a joint research team demonstrates that natural movements of the human hand and fingers can be generated with the same word corpus.
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Keyword(in English) Manual Alphabet / Hidden Markov Model / Corpus
Paper # SIP2005-94,SIS2005-43,SP2005-76
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Conference Date 2005/9/10(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Construction of a Corpus for HMM-based Continuous Manual Alphabet Recognition and Synthesis
Sub Title (in English)
Keyword(1) Manual Alphabet
Keyword(2) Hidden Markov Model
Keyword(3) Corpus
1st Author's Name Yuta EMOTO
1st Author's Affiliation Information Sience, Nagoya University()
2nd Author's Name Chiyomi MIYAJIMA
2nd Author's Affiliation Information Sience, Nagoya University
3rd Author's Name Katsunobu ITOU
3rd Author's Affiliation Information Sience, Nagoya University
4th Author's Name Kazuya TAKEDA
4th Author's Affiliation Information Sience, Nagoya University
Date 2005/9/10
Paper # SIP2005-94,SIS2005-43,SP2005-76
Volume (vol) vol.105
Number (no) 295
Page pp.pp.-
#Pages 6
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