Growing neural gas based conversation selection model for robot partner and human communication system

Shogo Yoshida, N. Kubota
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引用次数: 2

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.
基于神经气体的机器人伴侣与人类交流系统对话选择模型的增长
老年社会孤立已成为日本的一个重要问题。因此,引入机器人伴侣来支持社会孤立老年人的生活成为解决方案之一。本文讨论了基于生长神经气体(GNG)的会话选择模型。机器人伙伴由智能设备作为面部模块和具有两条手臂的机器人身体模块组成。我们首先结合老年人的生活支持讨论了机器人伴侣的必要性,同时讨论了对话选择模型与机器人伴侣的沟通能力表现之间的联系。接下来,我们提出了基于GNG的对话选择模型,从语音识别结果中确定机器人伙伴的话语。我们通过实验来讨论基于GNG和JS散度的方法的有效性。最后,我们展示了机器人搭档在使用所提出的方法进行对话时选择单词的能力。
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