Presentation 2011-05-20
Improvement of HMM-based Sign Language Recognition using Phonemic Structure of Japanese Sign Language
Shinji SAKO, Koki ARIGA, Tadashi KITAMURA,
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Abstract(in English) We work on automatic Japanese sign Language (JSL) recognition using Hidden Markov Model (HMM). An important issue for modeling sign is that how to determine the constituent element of sign (i.e., subunit) like "phoneme" in spoken language. We focused on special feature of sign language that JSL is composed of three types of phonological elements which is hand local information, position, and movement. In this report, we propose an efficiently method of generating subunit using multi-stream HMM which is correspond to phonological elements. An isolated 100/307 words recognition experiment has confirmed the effectiveness of our proposed method.
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Keyword(in English) sign language recognition / HMM / subunit / phonology / multi-stream HMM
Paper # WIT2011-8
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Committee WIT
Conference Date 2011/5/13(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Improvement of HMM-based Sign Language Recognition using Phonemic Structure of Japanese Sign Language
Sub Title (in English)
Keyword(1) sign language recognition
Keyword(2) HMM
Keyword(3) subunit
Keyword(4) phonology
Keyword(5) multi-stream HMM
1st Author's Name Shinji SAKO
1st Author's Affiliation Department of Computer Science and Engineering Graduate School of Engineering, Nagoya Institute of Technology()
2nd Author's Name Koki ARIGA
2nd Author's Affiliation Department of Computer Science and Engineering Graduate School of Engineering, Nagoya Institute of Technology
3rd Author's Name Tadashi KITAMURA
3rd Author's Affiliation Department of Computer Science and Engineering Graduate School of Engineering, Nagoya Institute of Technology
Date 2011-05-20
Paper # WIT2011-8
Volume (vol) vol.111
Number (no) 58
Page pp.pp.-
#Pages 6
Date of Issue