Affect-Enhancing Speech Characteristics for Robotic Communication

Abstract The attribution of mind to others, either humans or artificial agents, can be conceptualized along two dimensions: experience and agency. These dimensions are crucial in interactions with robots, influencing how they are perceived and treated by humans. Specifically, a higher attribution of agency to robots is associated with greater perceived responsibility, while a higher attribution of experience enhances sympathy towards them. One potential strategy to increase the attribution of experience to robots is the application of affective communication induced via prosody and verbal content such as emotional words and speech style. In two online studies ( N I = 30, N II = 60), participants listened to audio recordings in which robots introduced themselves. In study II, robot pictures were additionally presented to investigate potential matching effects between appearance and speech. Our results showed that both the use of emotional words and speaking expressively significantly increased the attributed experience of robots, whereas the attribution of agency remained unaffected. Findings further indicate that speaking expressively and using emotional words enhanced the perception of human-like qualities in artificial communication partners, with a more pronounced effect observed for technical robots compared to human-like robots. These insights can be used to improve the affective impact of synthesized robot speech and thus potentially increase the acceptance of robots to ensure long-term use.