Scaffolding for a Robot That Learns Reactions to Dialogue Acts

摘要

A dialogue act (DA) represents the meaning of an utterance at the illocutionary force level (Austin 1962) such as questions, requests, and greetings. Since DAs take charge of the most fundamental part of communication, we believe that the elucidation of DA learning mechanism is important for cognitive science and artificial intelligence. The purpose of this study is to let a robot learn to estimate DAs and to make a response based on them and to verify that scaffolding takes place when people teach the robot. The experimental results demonstrated that participants who continued interaction for a sufficiently long time gave scaffolding for the robot.