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Generating spatial referring expressions in a social robot: Dynamic vs. non-ambiguous

Wallbridge, Christopher D.; Lemaignan, S�verin; Senft, Emmanuel; Belpaeme, Tony

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Authors

Christopher D. Wallbridge

Profile image of Severin Lemaignan

Severin Lemaignan Severin.Lemaignan@uwe.ac.uk
Associate Professor in Social Robotics and AI

Emmanuel Senft

Tony Belpaeme



Abstract

Generating spatial referring expressions is key to allowing robots to communicate with people in an environment. The focus of most algorithms for generation is to create a non-ambiguous description, and how best to deal with the combination explosion this can create in a complex environment. However, this is not how people naturally communicate. Humans tend to give an under-specified description and then rely on a strategy of repair to reduce the number of possible locations or objects until the correct one is identified, what we refer to here as a dynamic description. We present here a method for generating these dynamic descriptions for Human Robot Interaction, using machine learning to generate repair statements. We also present a study with 61 participants in a task on object placement. This task was presented in a 2D environment that favored a non-ambiguous description. In this study we demonstrate that our dynamic method of communication can be more efficient for people to identify a location compared to one that is non-ambiguous.

Journal Article Type Article
Acceptance Date Jul 15, 2019
Online Publication Date Aug 2, 2019
Publication Date Aug 2, 2019
Deposit Date Nov 26, 2019
Publicly Available Date Nov 27, 2019
Journal Frontiers in Robotics and AI
Electronic ISSN 2296-9144
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 6
Article Number 67
DOI https://doi.org/10.3389/frobt.2019.00067
Keywords human robot interaction, natural language, spatial referring expressions, dynamic description, machine learning, user study
Public URL https://uwe-repository.worktribe.com/output/4742833

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Generating Spatial Referring Expressions in a Social Robot: Dynamic vs. Non-ambiguous (1.1 Mb)
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Licence
http://creativecommons.org/licenses/by/4.0/

Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
Copyright © 2019 Wallbridge, Lemaignan, Senft and Belpaeme. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the
original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.





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