Recent years have seen the advent of conversational humanoid robots. Implementing multiple robots is a promising approach for continuing human–robot conversations when a robot encounters speech-recognition errors. This strategy is effective for the user's verbal responses; however, people generally use nonverbal responses, such as nods or smiles, to respond to the interlocutor. In this study, we proposed a conversational strategy for twin robots in which the second robot recognized a human's nonverbal responses and interrupted the conversation by mentioning these responses. Moreover, we developed an interrogative dialogue system using simple nonverbal recognition modules. To verify the effectiveness of this conversational strategy, a subject-based experiment was conducted in which humans conversed with the two robots, and their impressions were evaluated through a questionnaire. We compared the outcomes under two conditions: whether the second robot's interruption was inserted or otherwise. Our results indicate that language-only ineffectiveness in responding to ambiguous responses regarding satisfaction and comprehension was mitigated. Thus, such a dialogue system is advantageous because it can facilitate robust conversation without relying solely on speech recognition.
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Sakai et al. (2024) studied this question.
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