Double-meaning agreements by two robots to conceal incoherent agreements to user's opinions

Abstract

In conversations between people and social robots, it is important that robots show agreements to user's opinions from the aspect of building relationships. However, robot's agreements are often incoherent to user's opinions due to speech recognition failures. This paper proposes a new approach called double-meaning agreement to conceal the incoherence. In this approach, we exploit an interaction protocol by two robots. The interaction protocol makes an agreement that has a double meaning and enables a user to interpret robot's incoherent agreement as coherent. To evaluate effects of double-meaning agreement, we conducted an experiment. The results showed that participants who talked with two robots using double-meaning agreement had better feelings of being understood by the robots than those who talked with one robot without double-meaning agreement. These findings will contribute to developing social robots to keep a conversation coherent and to build social relationships.