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Working with troubles and failures in conversation between humans and robots: workshop report

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posted on 2024-02-22, 10:12 authored by Frank Förster, Marta Romeo, Patrick Holthaus, Luke J. Wood, Christian Dondrup, Joel E. Fischer, Farhana Ferdousi Liza, Sara Kaszuba, Julian Hough, Birthe Nesset, Daniel Hernández García, Dimosthenis Kontogiorgos, Jennifer Williams, Elif Ecem Özkan, Pepita Barnard, Gustavo Berumen, Dominic Price, Sue Cobb, Martina Wiltschko, Lucien Tisserand, Martin Porcheron, Manuel Giuliani, Gabriel Skantze, Patrick G. T. Healey, Ioannis Papaioannou, Dimitra Gkatzia, Saul AlbertSaul Albert, Guanyu Huang, Vladislav Maraev, Epaminondas Kapetanios
This paper summarizes the structure and findings from the first Workshop on Troubles and Failures in Conversations between Humans and Robots. The workshop was organized to bring together a small, interdisciplinary group of researchers working on miscommunication from two complementary perspectives. One group of technology-oriented researchers was made up of roboticists, Human-Robot Interaction (HRI) researchers and dialogue system experts. The second group involved experts from conversation analysis, cognitive science, and linguistics. Uniting both groups of researchers is the belief that communication failures between humans and machines need to be taken seriously and that a systematic analysis of such failures may open fruitful avenues in research beyond current practices to improve such systems, including both speech-centric and multimodal interfaces. This workshop represents a starting point for this endeavour. The aim of the workshop was threefold: Firstly, to establish an interdisciplinary network of researchers that share a common interest in investigating communicative failures with a particular view towards robotic speech interfaces; secondly, to gain a partial overview of the “failure landscape” as experienced by roboticists and HRI researchers; and thirdly, to determine the potential for creating a robotic benchmark scenario for testing future speech interfaces with respect to the identified failures. The present article summarizes both the “failure landscape” surveyed during the workshop as well as the outcomes of the attempt to define a benchmark scenario.

Funding

Natural Language Generation for Low-resource Domains

Engineering and Physical Sciences Research Council

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CiViL: Common-sense- and Visually-enhanced natural Language generation

Engineering and Physical Sciences Research Council

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UKRI Trustworthy Autonomous Systems Hub

UK Research and Innovation

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Engineering and Physical Sciences Research Council [grant number EP/X009343/1]

A Collaborative Paradigm for Human Workers and Multi-Robot Teams in Precision Agriculture Systems

European Commission

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EXC 2002:  Science of Intelligence (SCIoI)

Deutsche Forschungsgemeinschaft

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The workshop, the outcomes of which are described in this paper, was funded by the UK Engineering and Physical Science Research Council (EPSRC) Robotics & Autonomous Systems Network (UK-RAS) Pump Priming programme under the project title “Charting the Limits and Developing Future Directions of Speech Interfaces for Robotics”

History

School

  • Social Sciences and Humanities

Department

  • Communication and Media

Published in

Frontiers in Robotics and AI

Volume

10

Publisher

Frontiers Media

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). 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.

Acceptance date

2023-11-09

Publication date

2023-12-01

Copyright date

2023

eISSN

2296-9144

Language

  • en

Depositor

Dr Saul Albert. Deposit date: 21 February 2024

Article number

1202306

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