Presentation 2005-09-21
Speech and Noise Recognition for Dialogue Robot in Ubiquitous Home Network
Ryuichi NISIMURA, Masaki CHIKAMA, Akihiro KOBAYASHI, Junji SATAKE, Hirotada UEDA,
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Abstract(in English) We have developed a dialogue robot "Phyno". It is aimed at becoming a familiar companion of users when living in the Ubiquitous-Home, in which various sensors and electric appliances provide context-aware services. This paper describes an architecture of a spoken dialogue interface containing dialogue strategies, a large vocabulary speech recognition, and a noise recognition. In the experiments, noise recognition method using the Gaussian Mixture Models (GMMs) obtained 94.4% correct classification rate.
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Keyword(in English) speech recognition / noise recognition / spoken dialogue robot interface / ubiquitous home
Paper # NLC2005-32,PRMU2005-59
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Conference Information
Committee PRMU
Conference Date 2005/9/14(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Speech and Noise Recognition for Dialogue Robot in Ubiquitous Home Network
Sub Title (in English)
Keyword(1) speech recognition
Keyword(2) noise recognition
Keyword(3) spoken dialogue robot interface
Keyword(4) ubiquitous home
1st Author's Name Ryuichi NISIMURA
1st Author's Affiliation Faculty of Systems Engineering, Wakayama University()
2nd Author's Name Masaki CHIKAMA
2nd Author's Affiliation National Institute of Information and Communications Technology (NICT)
3rd Author's Name Akihiro KOBAYASHI
3rd Author's Affiliation National Institute of Information and Communications Technology (NICT)
4th Author's Name Junji SATAKE
4th Author's Affiliation National Institute of Information and Communications Technology (NICT)
5th Author's Name Hirotada UEDA
5th Author's Affiliation National Institute of Information and Communications Technology (NICT)
Date 2005-09-21
Paper # NLC2005-32,PRMU2005-59
Volume (vol) vol.105
Number (no) 301
Page pp.pp.-
#Pages 6
Date of Issue