Backchannel Behavior Influences the Perceived Personality of Human and Artificial Communication Partners - Blomsma, Peter; Skantze, Gabriel; Swerts, Marc (Frontiers in Artificial Intelligence, 2022)
Different applications or contexts may require different settings for a conversational AI system, as it is clear that e.g. a child-oriented system would need a different interaction style than a warning system used in emergency situations. The current article focuses on the extent to which a system’s usability may benefit from variation in the personality it displays. To this end, we investigate whether variation in personality is signaled by differences in specific audiovisual feedback behavior, with a specific focus on embodied conversational agents. This article reports about two rating experiments in which participants judged the personalities (i) of human beings and (ii) of embodied conversational agents, where we were specifically interested in the role of variability in audiovisual cues. Our results show that personality perceptions of both humans and artificial communication partners are indeed influenced by the type of feedback behavior used. This knowledge could inform developers of conversational AI on how to also include personality in their feedback behavior generation algorithms, which could enhance the perceived personality and in turn generate a stronger sense of presence for the human interlocutor.