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, NielsKelleher, JohnMacNamee, Brian
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Date: Jan-2017
Online since: 2018-01-04T02:00:11Z
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
Journal: Advanced Robotics
Volume: 31
Start page: 243
End page: 257
Copyright (published version): 2017 Taylor and Francis
Keywords: Machine learningStatisticsDialogue systemsHuman-robot interactionPerception errorsDialogue
DOI: 10.1080/01691864.2016.1268973
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License:
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