机器人沟通风格设计与感知自信之间的差异

Luke Mckenzie-Mcharg, D. Kulić, Leimin Tian
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引用次数: 0

摘要

在人机交互过程中,机器人的自信感会影响人们对其可信度的评估,以及他们是否愿意听从机器人的建议。本研究提出了一种新的测量机器人感知自信的方法,既可以客观地评估一个人在数学测验任务中对机器人建议的依从性,也可以主观地评估一个人在不同假设场景中对机器人的感知和期望。受人际互动社会行为研究的启发,本文提出的测量方法从三个维度来评估机器人的感知自信,即社会自信、指向性和独立性。我们进行了一项探索性研究,使用众包来测试这种测量感知自信的有效性。特别是,参与者接触的机器人在拟人化和交流方式方面有所不同。交际风格是根据人类对通常与高自信或低自信相关的行为的研究而设计的。我们的结果证明了所提出的测量感知自信的有效性。观察到的客观和主观测量之间的差异突出了通过多种方法评估人类感知的必要性。此外,机器人的预期自信和感知自信之间的差距表明,人类交流理论与其对人机交互的适用性之间存在潜在的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discrepancies between designs of robot communicative styles and their perceived assertiveness
A robot’s perceived assertiveness can influence how people assess its credibility and their willingness to comply with its suggestions during human-robot interaction. This study proposes a novel measurement of the perceived assertiveness of a robot using both objective assessment of a person’s compliance to a robot’s suggestions in a math quiz task and subjective assessments of a person’s perception and expectation of a robot in different hypothetical scenarios. The proposed measurement evaluates perceived assertiveness of a robot in three dimensions inspired by social behavioral studies on human-human interaction, namely social assertiveness, directiveness, and independence. We conducted an exploratory study using crowdsourcing to test the efficacy of this proposed measurement of perceived assertiveness. In particular, participants were exposed to robots that differed in terms of their anthropomorphism and their communicative styles. The communicative styles are designed following human studies of behaviors that are commonly associated with high or low assertiveness. Our results demonstrated the validity of the proposed measurement of perceived assertiveness. The observed discrepancy between the objective and subjective measurements highlights the necessity of evaluating human perception through multiple approaches. Moreover, gaps between intended and perceived robot assertiveness indicate a potential gap between human communication theories and their applicability to human-robot interaction.
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