Multiple-Robot Conversational Patterns for Concealing Incoherent Responses

Abstract

Conversational robots, which are used in the fields of education, therapy, and in expositions, are expected to keep a user engaged in conversation. However, these robots sometimes utter comments that are irrelevant topic to the current context owing to a failure in recognizing the human user’s speech or intention. Such a sudden topic shift is considered to interfere with what we call the sense of conversation with which a person can feel as if he or she is participating in a conversation. In this paper, to reduce the interferes of the sudden topic shift, we propose to use multiple robots in a conversation, in which even an actually irrelevant, sudden topic shift sounds involving possible relevance to be shared with subjects in the ongoing conversation. To verify it, we conducted an experiment in which subjects experienced a conversation with either one or two robots and then evaluated their impression of the conversations. The experimental results showed that the subjects who talked with two robots felt less ignored by the robots, and had less difficulty in continuing the conversation with them, than those who talked with a single robot. Further analysis considering subjects’ social skills raised the possibility of an additional effect on robot coherence perception. Finally, we discuss a new disruption-tolerant conversational system design using multiple robots based on the experimental results.