Stepwise Acquisition of Dialogue Act Through Human-Robot Interaction

TL;DR

This study investigates how a robot can learn dialogue acts through stepwise human interaction, emphasizing scaffolding and adaptive learning to improve communication understanding.

Contribution

It demonstrates that robots can learn to estimate dialogue acts through human-guided scaffolding during interaction, even with unexpected teaching methods.

Findings

Robots quickly learned to respond to DAs with matching utterances.

Longer interactions improved the robot's DA estimation accuracy.

Unexpected scaffolding slowed initial learning but still led to eventual understanding.

Abstract

A dialogue act (DA) represents the meaning of an utterance at the illocutionary force level (Austin 1962) such as a question, a request, and a greeting. 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 verify that scaffolding takes place when a human teaches a robot, and to let a robot learn to estimate DAs and to make a response based on them step by step utilizing scaffolding provided by a human. To realize that, it is necessary for the robot to detect changes in utterance and rewards given by the partner and continue learning accordingly. Experimental results demonstrated that participants who continued interaction for a sufficiently long time often gave scaffolding for the robot. Although the number of experiments is still insufficient to obtain a definite conclusion, we observed that 1) the robot quickly learned to respond to DAs in most cases if the participants only spoke utterances that match the situation, 2) in the case of participants who builds scaffolding differently from what we assumed, learning did not proceed quickly, and 3) the robot could learn to estimate DAs almost exactly if the participants kept interaction for a sufficiently long time even if the scaffolding was unexpected.