Turn-Taking Strategies for Human-Robot Peer-Learning Dialogue.

In this paper, we apply the contribution model of grounding to a corpus of human-human peer-mentoring dialogues. From this analysis, we propose effective turn-taking strategies for human-robot interaction with a teachable robot. Specifically, we focus on (1) how robots can encourage humans to present and (2) how robots can signal that they are going to begin a new presentation. We evaluate the strategies against a corpus of human-robot dialogues and offer three guidelines for teachable robots to follow to achieve more human-like collaborative dialogue.