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Article

Incremental natural language processing for HRI

Authors:

Matthias ScheutzAuthors Info & Claims

HRI '07: Proceedings of the ACM/IEEE international conference on Human-robot interaction

Pages 263 - 270

https://doi.org/10.1145/1228716.1228752

Published: 10 March 2007 Publication History

Abstract

Robots that interact with humans face-to-face using natural language need to be responsive to the way humans use language in those situations. We propose a psychologically-inspired natural language processing system for robots which performs incremental semantic interpretation of spoken utterances, integrating tightly with the robot's perceptual and motor systems.

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Cited By

Liu RGuo YJin RZhang X(2024)A Review of Natural-Language-Instructed Robot Execution SystemsAI10.3390/ai50300485:3(948-989)Online publication date: 26-Jun-2024
https://doi.org/10.3390/ai5030048
Williams TMatuszek CMead RDepalma N(2024)Scarecrows in Oz: The Use of Large Language Models in HRIACM Transactions on Human-Robot Interaction10.1145/360626113:1(1-11)Online publication date: 31-Mar-2024
https://dl.acm.org/doi/10.1145/3606261
Li SSiva SMott TWilliams TZhang HDantam N(2023)Failure Explanation in Privacy-Sensitive Contexts: An Integrated Systems Approach2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)10.1109/RO-MAN57019.2023.10309501(2328-2335)Online publication date: 28-Aug-2023
https://doi.org/10.1109/RO-MAN57019.2023.10309501
Show More Cited By

Index Terms

Incremental natural language processing for HRI
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Information

Published In

cover image ACM Conferences

HRI '07: Proceedings of the ACM/IEEE international conference on Human-robot interaction

March 2007

392 pages

ISBN:9781595936172

DOI:10.1145/1228716

General Chairs:
Cynthia Breazeal
Massachusetts Institute of Technology, USA
,
Alan C. Schultz
Naval Research Laboratory, USA
,
Program Chairs:
Terry Fong
NASA Ames Research Center, USA
,
Sara Kiesler
Carnegie Mellon University, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 March 2007

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HRI07

Sponsor:

HRI07: International Conference on Human Robot Interaction

March 10 - 12, 2007

Virginia, Arlington, USA

Acceptance Rates

HRI '07 Paper Acceptance Rate 22 of 101 submissions, 22%;

Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Cited By

Liu RGuo YJin RZhang X(2024)A Review of Natural-Language-Instructed Robot Execution SystemsAI10.3390/ai50300485:3(948-989)Online publication date: 26-Jun-2024
https://doi.org/10.3390/ai5030048
Williams TMatuszek CMead RDepalma N(2024)Scarecrows in Oz: The Use of Large Language Models in HRIACM Transactions on Human-Robot Interaction10.1145/360626113:1(1-11)Online publication date: 31-Mar-2024
https://dl.acm.org/doi/10.1145/3606261
Li SSiva SMott TWilliams TZhang HDantam N(2023)Failure Explanation in Privacy-Sensitive Contexts: An Integrated Systems Approach2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)10.1109/RO-MAN57019.2023.10309501(2328-2335)Online publication date: 28-Aug-2023
https://doi.org/10.1109/RO-MAN57019.2023.10309501
Jackson RWilliams T(2022)Enabling Morally Sensitive Robotic Clarification RequestsACM Transactions on Human-Robot Interaction10.1145/350379511:2(1-18)Online publication date: 4-Mar-2022
https://dl.acm.org/doi/10.1145/3503795
Scheutz MThielstrom RAbrams M(2022)Transparency through Explanations and Justifications in Human-Robot Task-Based CommunicationsInternational Journal of Human–Computer Interaction10.1080/10447318.2022.209108638:18-20(1739-1752)Online publication date: 27-Jul-2022
https://doi.org/10.1080/10447318.2022.2091086
Blake Jackson RLi SBalajee Banisetty SSiva SZhang HDantam NWilliams T(2021)An Integrated Approach to Context-Sensitive Moral Cognition in Robot Cognitive Architectures2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS51168.2021.9636434(1911-1918)Online publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1109/IROS51168.2021.9636434
Hinaut XTwiefel J(2020)Teach Your Robot Your Language! Trainable Neural Parser for Modeling Human Sentence Processing: Examples for 15 LanguagesIEEE Transactions on Cognitive and Developmental Systems10.1109/TCDS.2019.295700612:2(179-188)Online publication date: Jun-2020
https://doi.org/10.1109/TCDS.2019.2957006
Biswas MRomeo MCangelosi AJones R(2019)Are older people any different from younger people in the way they want to interact with robots? Scenario based surveyJournal on Multimodal User Interfaces10.1007/s12193-019-00306-x14:1(61-72)Online publication date: 24-Jul-2019
https://doi.org/10.1007/s12193-019-00306-x
Williams TYazdani FSuresh PScheutz MBeetz M(2019)Dempster-Shafer theoretic resolution of referential ambiguityAutonomous Robots10.1007/s10514-018-9795-543:2(389-414)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10514-018-9795-5
Moetesum MSiddiqi I(2018)Socially Believable RobotsHuman-Robot Interaction - Theory and Application10.5772/intechopen.71375Online publication date: 4-Jul-2018
https://doi.org/10.5772/intechopen.71375
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