Talk to Me: Verbal Communication Improves Perceptions of Friendship and Social Presence in Human-Robot Interaction

The ability of social agents, be it virtually-embodied avatars or physically-embodied robots, to display social behavior and interact with their users in a natural way represents an important factor in how effective such agents are during interactions. In particular, endowing the agent with effective communicative abilities, well-suited for the target application or task, can make a significant difference in how users perceive the agent, especially when the agent needs to interact in complex social environments. In this work, we consider how two core input communication modalities present in human-robot interaction-speech recognition and touch-based selection-shape users' perceptions of the agent. We design a short interaction in order to gauge adolescents' reaction to the input communication modality employed by a robot intended as a long-term companion for motivating them to engage in daily physical activity. A study with n = 52 participants shows that adolescents perceive the robot as more of a friend and more socially present in the speech recognition condition than in the touch-based selection one. Our results highlight the advantages of using speech recognition as an input communication modality even when this represents the less robust choice, and the importance of investigating how to best do so.