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Conference Paper/Proceeding/Abstract 362 views

Keep it Short: A Comparison of Voice Assistants’ Response Behavior

Gabriel Haas, Michael Rietzler, Matt Jones, Enrico Rukzio, Matt Jones Orcid Logo

CHI Conference on Human Factors in Computing Systems

Swansea University Author: Matt Jones Orcid Logo

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DOI (Published version): 10.1145/3491102.3517684

Abstract

Voice assistants (VAs) are present in homes, smartphones, and cars. They allow users to perform tasks without graphical or tactile user interfaces, as they are designed for natural language interaction. However, we found that currently, VAs are emulating human behavior by responding in complete sent...

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Published in: CHI Conference on Human Factors in Computing Systems
ISBN: 978-1-4503-9157-3
Published: New York, NY, USA ACM 2022
Online Access: http://dx.doi.org/10.1145/3491102.3517684
URI: https://cronfa.swan.ac.uk/Record/cronfa60205
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first_indexed 2022-06-27T16:22:04Z
last_indexed 2023-01-13T19:20:09Z
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spelling 2022-10-31T14:40:44.7736680 v2 60205 2022-06-14 Keep it Short: A Comparison of Voice Assistants’ Response Behavior 10b46d7843c2ba53d116ca2ed9abb56e 0000-0001-7657-7373 Matt Jones Matt Jones true false 2022-06-14 SCS Voice assistants (VAs) are present in homes, smartphones, and cars. They allow users to perform tasks without graphical or tactile user interfaces, as they are designed for natural language interaction. However, we found that currently, VAs are emulating human behavior by responding in complete sentences, limiting the design options, and preventing VAs from meeting their full potential as a utilitarian tool. We implemented a VA that handles requests in three response styles: two differing short keyword-based response styles and a full-sentence baseline. In a user study, 72 participants interacted with our VA by issuing eight requests. Results show that the short responses were perceived similarly useful and likable while being perceived as more efficient, especially for commands, and sometimes better to comprehend than the baseline. To achieve widespread adoption, we argue that VAs should be customizable and adapt to users instead of always responding in full sentences. Conference Paper/Proceeding/Abstract CHI Conference on Human Factors in Computing Systems ACM New York, NY, USA 978-1-4503-9157-3 29 4 2022 2022-04-29 10.1145/3491102.3517684 http://dx.doi.org/10.1145/3491102.3517684 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2022-10-31T14:40:44.7736680 2022-06-14T09:39:22.5004558 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Gabriel Haas 1 Michael Rietzler 2 Matt Jones 3 Enrico Rukzio 4 Matt Jones 0000-0001-7657-7373 5
title Keep it Short: A Comparison of Voice Assistants’ Response Behavior
spellingShingle Keep it Short: A Comparison of Voice Assistants’ Response Behavior
Matt Jones
title_short Keep it Short: A Comparison of Voice Assistants’ Response Behavior
title_full Keep it Short: A Comparison of Voice Assistants’ Response Behavior
title_fullStr Keep it Short: A Comparison of Voice Assistants’ Response Behavior
title_full_unstemmed Keep it Short: A Comparison of Voice Assistants’ Response Behavior
title_sort Keep it Short: A Comparison of Voice Assistants’ Response Behavior
author_id_str_mv 10b46d7843c2ba53d116ca2ed9abb56e
author_id_fullname_str_mv 10b46d7843c2ba53d116ca2ed9abb56e_***_Matt Jones
author Matt Jones
author2 Gabriel Haas
Michael Rietzler
Matt Jones
Enrico Rukzio
Matt Jones
format Conference Paper/Proceeding/Abstract
container_title CHI Conference on Human Factors in Computing Systems
publishDate 2022
institution Swansea University
isbn 978-1-4503-9157-3
doi_str_mv 10.1145/3491102.3517684
publisher ACM
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://dx.doi.org/10.1145/3491102.3517684
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description Voice assistants (VAs) are present in homes, smartphones, and cars. They allow users to perform tasks without graphical or tactile user interfaces, as they are designed for natural language interaction. However, we found that currently, VAs are emulating human behavior by responding in complete sentences, limiting the design options, and preventing VAs from meeting their full potential as a utilitarian tool. We implemented a VA that handles requests in three response styles: two differing short keyword-based response styles and a full-sentence baseline. In a user study, 72 participants interacted with our VA by issuing eight requests. Results show that the short responses were perceived similarly useful and likable while being perceived as more efficient, especially for commands, and sometimes better to comprehend than the baseline. To achieve widespread adoption, we argue that VAs should be customizable and adapt to users instead of always responding in full sentences.
published_date 2022-04-29T04:18:07Z
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score 10.998093

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