Robot perception errors and human resolution strategies in situated human-robot dialogue

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Title: Robot perception errors and human resolution strategies in situated human-robot dialogue
Authors: Schutte, Niels
Kelleher, John
MacNamee, Brian
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Date: Jan-2017
Abstract: We performed an experiment in which human participants interacted through a natural language dialogue interface with a simulated robot to fulfil a series of object manipulation tasks. We introduced errors into the robot’s perception, and observed the resulting problems in the dialogues and their resolutions. We then introduced different methods for the user to request information about the robot’s understanding of the environment. We quantify the impact of perception errors on the dialogues, and investigate resolution attempts by users at a structural level and at the level of referring expressions.
Type of material: Journal Article
Publisher: Taylor and Francis
Copyright (published version): 2017 Taylor and Francis
Keywords: Machine learning;Statistics;Dialogue systems;Human-robot interaction;Perception errors;Dialogue
DOI: 10.1080/01691864.2016.1268973
Language: en
Status of Item: Peer reviewed
Appears in Collections:Insight Research Collection

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