Perugia Giulia, Paetzel-Prüsmann Maike, Hupont Isabelle, Varni Giovanna, Chetouani Mohamed, Peters Christopher Edward, Castellano Ginevra
Human Technology Interaction Group, Eindhoven University of Technology, Eindhoven, Netherlands.
Uppsala Social Robotics Lab, Department of Information Technology, Uppsala University, Uppsala, Sweden.
Front Robot AI. 2021 Nov 17;8:699090. doi: 10.3389/frobt.2021.699090. eCollection 2021.
In this paper, we present a study aimed at understanding whether the embodiment and humanlikeness of an artificial agent can affect people's spontaneous and instructed mimicry of its facial expressions. The study followed a mixed experimental design and revolved around an emotion recognition task. Participants were randomly assigned to one level of humanlikeness (between-subject variable: humanlike, characterlike, or morph facial texture of the artificial agents) and observed the facial expressions displayed by three artificial agents differing in embodiment (within-subject variable: video-recorded robot, physical robot, and virtual agent) and a human (control). To study both spontaneous and instructed facial mimicry, we divided the experimental sessions into two phases. In the first phase, we asked participants to observe and recognize the emotions displayed by the agents. In the second phase, we asked them to look at the agents' facial expressions, replicate their dynamics as closely as possible, and then identify the observed emotions. In both cases, we assessed participants' facial expressions with an automated Action Unit (AU) intensity detector. Contrary to our hypotheses, our results disclose that the agent that was perceived as the least uncanny, and most anthropomorphic, likable, and co-present, was the one spontaneously mimicked the least. Moreover, they show that instructed facial mimicry negatively predicts spontaneous facial mimicry. Further exploratory analyses revealed that spontaneous facial mimicry appeared when participants were less certain of the emotion they recognized. Hence, we postulate that an emotion recognition goal can flip the social value of facial mimicry as it transforms a likable artificial agent into a distractor. Further work is needed to corroborate this hypothesis. Nevertheless, our findings shed light on the functioning of human-agent and human-robot mimicry in emotion recognition tasks and help us to unravel the relationship between facial mimicry, liking, and rapport.
在本文中,我们展示了一项旨在了解人工代理的具身性和类人性是否会影响人们对其面部表情的自发模仿和指令性模仿的研究。该研究采用了混合实验设计,并围绕一项情感识别任务展开。参与者被随机分配到类人性的一个水平(组间变量:类人、类角色或人工代理的变形面部纹理),并观察由三个具身性不同的人工代理(组内变量:视频记录机器人、实体机器人和虚拟代理)以及一个人类(对照组)所展示的面部表情。为了研究自发和指令性面部模仿,我们将实验环节分为两个阶段。在第一阶段,我们要求参与者观察并识别代理所展示的情感。在第二阶段,我们要求他们观看代理的面部表情,尽可能紧密地复制其动态,然后识别所观察到的情感。在这两种情况下,我们都使用自动动作单元(AU)强度检测器来评估参与者的面部表情。与我们的假设相反,我们的结果表明,被认为最不怪异、最具拟人化、最讨人喜欢且最具共在感的代理,却是被自发模仿得最少的。此外,结果还表明,指令性面部模仿对自发面部模仿具有负向预测作用。进一步的探索性分析显示,当参与者对自己识别出的情感不太确定时,会出现自发面部模仿。因此,我们推测,情感识别目标可以改变面部模仿的社会价值,因为它将一个讨人喜欢的人工代理变成了一个干扰因素。需要进一步的研究来证实这一假设。尽管如此,我们的研究结果揭示了在情感识别任务中人与代理以及人与机器人模仿的运作方式,并帮助我们理清面部模仿、喜爱和融洽关系之间的联系。