Dimensional Design of Emotive Sounds for Robots

Non-Linguistic Utterances (NLUs) are essential parts of emotive exchanges, not only in human-human interactions but also in the context of human-robot interactions. This research aims to deepen our understanding of emotive sounds for the domain of human-robot exchanges. We investigated the connections between certain audio qualities and the perception of emotional arousal and pleasure, designing a novel mapping of musical and prosodic audio parameters to a dimensional model of emotion which allows a robot to express a range of emotions. To assess the emotive sounds, we conducted an end-user evaluation in which participants were asked to interpret the emotive NLUs conveyed by robots. In the evaluation we examined 4 archetypal emotions: excitement, contentment, sadness, and anger. We placed participants’ responses within the pleasure-arousal affect grid to analyze the distinctiveness of the emotive sounds. The study revealed that participants consistently associated excited, sad and angry NLUs with significantly different emotional states but did not do so for content NLUs. These findings contribute valuable insights into how to design NLUs which can enhance the emotional depth of human-robot interactions, with potential applications across various domains.CCS CONCEPTS• Human-centered computing → Auditory feedback; User studies; • Computer systems organization → Robotics; • Applied computing → Sound and music computing.