Who to Teach a Robot to Facilitate Multi-party Social Interactions?

Jouh Yeong Chew, Keisuke Nakamura
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Abstract

One salient function of social robots is to play the role of facilitator to enhance the harmony state of multi-party social interactions so that every human participant is encouraged and motivated to engage actively. However, it is challenging to handcraft the behavior of social robots to achieve this objective. One promising approach is for the robot to learn from human teachers. This paper reports the findings of an empirical test to determine the optimal experiment condition for a robot to learn verbal and nonverbal strategies to facilitate a multi-party interaction. First, the modified L8 Orthogonal Array (OA) is used to design a fractional factorial experiment condition using factors like the type of human facilitator, group size and stimulus type. The response of OA is the harmony state explicitly defined using the speech turn-taking between speakers and represented using metrics extracted from the first order Markov transition matrix. Analyses of Main Effects and ANOVA suggest the type of human facilitator and group size are significant factors affecting the harmony state. Therefore, we propose the optimal experiment condition to train a facilitator robot using high school teachers as human teachers and group size larger than four participants.
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谁教机器人促进多方社会互动?
社交机器人的一个突出功能是扮演促进者的角色,增强多方社会互动的和谐状态,从而鼓励和激励每个人类参与者积极参与。然而,手工制作社交机器人的行为来实现这一目标是具有挑战性的。一种很有希望的方法是让机器人向人类老师学习。本文报告了一项实证测试的结果,以确定机器人学习语言和非语言策略以促进多方互动的最佳实验条件。首先,利用改进的L8正交阵列(OA)设计分数析因实验条件,考虑人的引导者类型、群体规模和刺激类型等因素。OA的响应是使用说话者之间的语音轮流显式定义的和谐状态,并使用从一阶马尔可夫转移矩阵中提取的度量来表示。主效应分析和方差分析表明,协调人类型和团队规模是影响和谐状态的重要因素。因此,我们提出了以高中教师为真人教师,团队规模大于4人,训练引导员机器人的最佳实验条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Transactions on Human-Robot Interaction
ACM Transactions on Human-Robot Interaction Computer Science-Artificial Intelligence
CiteScore
7.70
自引率
5.90%
发文量
65
期刊介绍: ACM Transactions on Human-Robot Interaction (THRI) is a prestigious Gold Open Access journal that aspires to lead the field of human-robot interaction as a top-tier, peer-reviewed, interdisciplinary publication. The journal prioritizes articles that significantly contribute to the current state of the art, enhance overall knowledge, have a broad appeal, and are accessible to a diverse audience. Submissions are expected to meet a high scholarly standard, and authors are encouraged to ensure their research is well-presented, advancing the understanding of human-robot interaction, adding cutting-edge or general insights to the field, or challenging current perspectives in this research domain. THRI warmly invites well-crafted paper submissions from a variety of disciplines, encompassing robotics, computer science, engineering, design, and the behavioral and social sciences. The scholarly articles published in THRI may cover a range of topics such as the nature of human interactions with robots and robotic technologies, methods to enhance or enable novel forms of interaction, and the societal or organizational impacts of these interactions. The editorial team is also keen on receiving proposals for special issues that focus on specific technical challenges or that apply human-robot interaction research to further areas like social computing, consumer behavior, health, and education.
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