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A Method of Combination of Language Understanding with Touch-Based Communication Robots

机译:一种将语言理解与基于触摸的通信机器人相结合的方法

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Studies of robots which aim to entertain and to be conversational partners of the live-alone become very important. The robots are classified into DBC (Dialogue-Based Communication) robots and TBC (Touch-Based Communication) robots. DBC robots have an effect to be conversational partners. A typical application of TBC robots is Paro (a baby harp seal robot) which has an effect to entertain humans. The combination of DBC and TBC will be able to achieve both a conversational ability and an entertaining effect, but there is no study of combination of DBC and TBC. This paper proposes a response algorithm that can combine conversational information and touch information from humans. Criterions for estimation are defined as follows: FFV (Familiarity Factor Value), EFV (Enjoyment Factor Value), CR (Concentration Rate), ER (Expression Rate), and RR (Recognition Rate). FFV and EFV are total ratings for questionnaire related to familiarity and enjoyment factors, respectively. CR measures attention for humans. ER is the interest of communication with robots by representing Level 2 (laugh with opening one’s mouse), Level 1 (smile), and Level 0 (expressionless). RR is recognition ability for voices and touch actions. From the experiment for impressions of robot responses with 11 subjects, it turns out that the proposed method with combination of DBC and TBC is improved by 20.7 points in FFV, and by 12.6 points in EFV compared to only TBC. From the robot communication experiment, it turns out that the proposed method is improved by 8 points in the ER, by 5.3 points in the ER with Level 2, and by 24.5 points in the RR compared to only DBC.
机译:旨在娱乐并成为独居对话伙伴的机器人的研究变得非常重要。机器人分为DBC(基于对话框的通信)机器人和TBC(基于触摸的通信)机器人。 DBC机器人可以成为对话伙伴。 TBC机器人的典型应用是Paro(婴儿竖琴海豹机器人),它具有娱乐人类的作用。 DBC和TBC的结合将能够同时实现对话能力和娱乐效果,但是还没有DBC和TBC结合的研究。本文提出了一种可以将人类的对话信息和触摸信息相结合的响应算法。估计标准定义如下:FFV(熟悉因素值),EFV(享受因素值),CR(集中度),ER(表达率)和RR(识别率)。 FFV和EFV分别是与熟悉程度和娱乐程度相关的问卷的总评分。 CR衡量对人类的关注。 ER代表2级(打开鼠标笑),1级(微笑)和0级(无表情),这是与机器人进行交流的兴趣。 RR是语音和触摸动作的识别能力。从对11个对象的机器人反应印象的实验中可以看出,与仅使用TBC相比,将DBC和TBC结合使用的方法在FFV中提高了20.7分,在EFV中提高了12.6分。从机器人通讯实验中可以看出,与仅DBC相比,该方法在ER中提高了8点,在2级的ER中提高了5.3点,在RR中提高了24.5点。

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