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Title: 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.  more » « less
Award ID(s):
1637947
PAR ID:
10076262
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Proceedings of the SIGDIAL 2018 Conference
Page Range / eLocation ID:
119 - 129
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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