Behavioral and Emotional Spoken Cues Related to Mental States in Human-Robot Social Interaction

Understanding human behavioral and emotional cues occurring in interaction has become a major research interest due to the emergence of numerous applications such as in social robotics. While there is agreement across different theories that some behavioral signals are involved in communicating information, there is a lack of consensus regarding their specificity, their universality, and whether they convey emotions, affective, cognitive, mental states or all of those. Our goal in this study is to explore the relationship between behavioral and emotional cues extracted from speech (e.g., laughter, speech duration, negative emotions) with different communicative information about the human participant. This study is based on a corpus of audio/video data of humorous interactions between the nao{} robot and 37 human participants. Participants filled three questionnaires about their personality, sense of humor and mental states regarding the interaction. This work reveals the existence of many links between behavioral and emotional cues and the mental states reported by human participants through self-report questionnaires. However, we have not found a clear connection between reported mental states and participants profiles.