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A Multimodal Approach to Assessing User Experiences with Agent Helpers / Leigh Clark; Abdulmalik Ofemile; Svenja Adolphs; Tom Rodden

ACM Transactions on Interactive Intelligent Systems, Volume: 6, Issue: 4, Pages: 1 - 31

Swansea University Author: Leigh, Clark

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DOI (Published version): 10.1145/2983926

Abstract

The study of agent helpers using linguistic strategies such as vague language and politeness has often come across obstacles. One of these is the quality of the agent's voice and its lack of appropriate fit for using these strategies. The first approach of this article compares human vs. synthe...

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Published in: ACM Transactions on Interactive Intelligent Systems
ISSN: 2160-6455 2160-6463
Published: Association for Computing Machinery (ACM) 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa52487
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spelling 2020-09-25T15:08:39.9437870 v2 52487 2019-10-17 A Multimodal Approach to Assessing User Experiences with Agent Helpers 004ef41b90854a57a498549a462f13a0 0000-0002-9237-1057 Leigh Clark Leigh Clark true false 2019-10-17 SCS The study of agent helpers using linguistic strategies such as vague language and politeness has often come across obstacles. One of these is the quality of the agent's voice and its lack of appropriate fit for using these strategies. The first approach of this article compares human vs. synthesised voices in agents using vague language. This approach analyses the 60,000-word text corpus of participant interviews to investigate the differences of user attitudes towards the agents, their voices and their use of vague language. It discovers that while the acceptance of vague language is still met with resistance in agent instructors, using a human voice yields more positive results than the synthesised alternatives. The second approach in this article discusses the development of a novel multimodal corpus of video and text data to create multiple analyses of human-agent interaction in agent-instructed assembly tasks. The second approach analyses user spontaneous facial actions and gestures during their interaction in the tasks. It found that agents are able to elicit these facial actions and gestures and posits that further analysis of this nonverbal feedback may help to create a more adaptive agent. Finally, the approaches used in this article suggest these can contribute to furthering the understanding of what it means to interact with software agents. Journal Article ACM Transactions on Interactive Intelligent Systems 6 4 1 31 Association for Computing Machinery (ACM) 2160-6455 2160-6463 Human-agent interaction, vague language, instruction giving, gestures, facial actions, emotions 26 12 2016 2016-12-26 10.1145/2983926 The figures in the openly available version of the PDF are skewed. The publisher's version presents a better view of the images. COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2020-09-25T15:08:39.9437870 2019-10-17T13:51:46.9397774 College of Science Computer Science Leigh Clark 1 Abdulmalik Ofemile 2 Svenja Adolphs 3 Tom Rodden 4 Leigh Clark 0000-0002-9237-1057 5 52487__15659__623d4e5410f14306bedfe9d85c8ad725.pdf JULYEDIT1_TiiSSubmissionMay2016.pdf 2019-10-17T14:25:23.3330000 Output 750436 application/pdf Accepted Manuscript true true eng
title A Multimodal Approach to Assessing User Experiences with Agent Helpers
spellingShingle A Multimodal Approach to Assessing User Experiences with Agent Helpers
Leigh, Clark
title_short A Multimodal Approach to Assessing User Experiences with Agent Helpers
title_full A Multimodal Approach to Assessing User Experiences with Agent Helpers
title_fullStr A Multimodal Approach to Assessing User Experiences with Agent Helpers
title_full_unstemmed A Multimodal Approach to Assessing User Experiences with Agent Helpers
title_sort A Multimodal Approach to Assessing User Experiences with Agent Helpers
author_id_str_mv 004ef41b90854a57a498549a462f13a0
author_id_fullname_str_mv 004ef41b90854a57a498549a462f13a0_***_Leigh, Clark
author Leigh, Clark
author2 Leigh Clark
Abdulmalik Ofemile
Svenja Adolphs
Tom Rodden
Leigh Clark
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institution Swansea University
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publisher Association for Computing Machinery (ACM)
college_str College of Science
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hierarchy_parent_title College of Science
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description The study of agent helpers using linguistic strategies such as vague language and politeness has often come across obstacles. One of these is the quality of the agent's voice and its lack of appropriate fit for using these strategies. The first approach of this article compares human vs. synthesised voices in agents using vague language. This approach analyses the 60,000-word text corpus of participant interviews to investigate the differences of user attitudes towards the agents, their voices and their use of vague language. It discovers that while the acceptance of vague language is still met with resistance in agent instructors, using a human voice yields more positive results than the synthesised alternatives. The second approach in this article discusses the development of a novel multimodal corpus of video and text data to create multiple analyses of human-agent interaction in agent-instructed assembly tasks. The second approach analyses user spontaneous facial actions and gestures during their interaction in the tasks. It found that agents are able to elicit these facial actions and gestures and posits that further analysis of this nonverbal feedback may help to create a more adaptive agent. Finally, the approaches used in this article suggest these can contribute to furthering the understanding of what it means to interact with software agents.
published_date 2016-12-26T04:06:00Z
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