DocumentCode :
1797469
Title :
Growing neural gas based conversation selection model for robot partner and human communication system
Author :
Yoshida, Sigeru ; Kubota, Naoyuki
Author_Institution :
Dept. of Syst. Design, Tokyo Metropolitan Univ., Tokyo, Japan
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
1
Lastpage :
5
Abstract :
Elderly people with socially isolated has become an important problem in Japan. Therefore, the introduction robot partner for supporting socially isolated elderly people´s life become of the solutions. This paper discusses conversation selection model using Growing Neural Gas(GNG). The robot partner is composed of a smart device used as a face module and the robot body module with two arms. First we discuss the necessity of robot partner in conjunction with elderly people life support, while we also discuss the connection between conversation selection model and robot partner´s communication ability performance. Next, we propose conversation selection model using GNG for determining robot partner´s utterance from voice recognition result. We conduct experiments to discuss the effectiveness of the proposed method based on GNG and JS divergence. Finally, we show the robot partner´s capability in selecting words while performing conversation using the proposed method.
Keywords :
geriatrics; human-robot interaction; neural nets; service robots; speech recognition; GNG; JS divergence; conversation selection model; elderly people life support; face module; growing neural gas; human communication system; robot body module; robot partner; robot partners communication ability performance; smart device; voice recognition; Correlation; Internet; Robot sensing systems; Senior citizens; Speech recognition; Conversation Selection Model; Growing Neural Gas; Robot Partner;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotic Intelligence In Informationally Structured Space (RiiSS), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/RIISS.2014.7009166
Filename :
7009166
Link To Document :
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