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Conference Paper/Proceeding/Abstract 792 views 99 downloads

Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers

Thomas Reitmaier Orcid Logo, Electra Wallington, Ondrej Klejch, Nina Markl, Léa-Marie Lam-Yee-Mui, Jen Pearson Orcid Logo, Matt Jones Orcid Logo, Peter Bell, Simon Robinson Orcid Logo

ACM CHI Conference on Human Factors in Computing Systems: CHI' 23, Pages: 1 - 17

Swansea University Authors: Thomas Reitmaier Orcid Logo, Jen Pearson Orcid Logo, Matt Jones Orcid Logo, Simon Robinson Orcid Logo

DOI (Published version): 10.1145/3544548.3581385

Abstract

In this paper we develop approaches to automatic speech recognition (ASR) development that suit the needs and functions of underheard language speakers. Our novel contribution to HCI is to show how community-engagement can surface key technical and social issues and opportunities for more efective s...

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Published in: ACM CHI Conference on Human Factors in Computing Systems: CHI' 23
ISBN: 978-1-4503-9421-5/23/04
Published: ACM 2023
URI: https://cronfa.swan.ac.uk/Record/cronfa62395
first_indexed 2023-01-23T10:21:39Z
last_indexed 2024-11-14T12:20:53Z
id cronfa62395
recordtype SURis
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spelling 2024-10-18T16:35:20.8337574 v2 62395 2023-01-23 Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers ccd66b64d11d76b9cd8b28e9d42a0ff0 0000-0003-2078-6699 Thomas Reitmaier Thomas Reitmaier true false 6d662d9e2151b302ed384b243e2a802f 0000-0002-1960-1012 Jen Pearson Jen Pearson true false 10b46d7843c2ba53d116ca2ed9abb56e 0000-0001-7657-7373 Matt Jones Matt Jones true false cb3b57a21fa4e48ec633d6ba46455e91 0000-0001-9228-006X Simon Robinson Simon Robinson true false 2023-01-23 MACS In this paper we develop approaches to automatic speech recognition (ASR) development that suit the needs and functions of underheard language speakers. Our novel contribution to HCI is to show how community-engagement can surface key technical and social issues and opportunities for more efective speech-based systems. We introduce a bespoke toolkit of technologies and showcase how we utilised the toolkit to engage communities of under-heard language speakers; and, through that engagement process, situate key aspects of ASR development in community contexts. The toolkit consists of (1) an information appliance to facilitate spoken-data collection on topics of community interest, (2) a mobile app to create crowdsourced transcripts of collected data, and (3) demonstrator systems to showcase ASR capabilities and to feed back research results to community members. Drawing on the sensibilities we cultivated through this research, we present a series of challenges to the orthodoxy of state-of-the-art approaches to ASR development. Conference Paper/Proceeding/Abstract ACM CHI Conference on Human Factors in Computing Systems: CHI' 23 1 17 ACM 978-1-4503-9421-5/23/04 Text/speech/language, automatic speech recognition, mobile devices: phones/tablets 23 4 2023 2023-04-23 10.1145/3544548.3581385 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) UKRI (EP/T024976/1) 2024-10-18T16:35:20.8337574 2023-01-23T10:20:07.8635873 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Thomas Reitmaier 0000-0003-2078-6699 1 Electra Wallington 2 Ondrej Klejch 3 Nina Markl 4 Léa-Marie Lam-Yee-Mui 5 Jen Pearson 0000-0002-1960-1012 6 Matt Jones 0000-0001-7657-7373 7 Peter Bell 8 Simon Robinson 0000-0001-9228-006X 9 62395__26881__e485e0f343b448309b02477abfd5d603.pdf Situating-Automatic-Speech-Recognition.pdf 2023-03-17T14:07:34.1310898 Output 2092884 application/pdf Version of Record true true eng
title Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
spellingShingle Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
Thomas Reitmaier
Jen Pearson
Matt Jones
Simon Robinson
title_short Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
title_full Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
title_fullStr Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
title_full_unstemmed Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
title_sort Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
author_id_str_mv ccd66b64d11d76b9cd8b28e9d42a0ff0
6d662d9e2151b302ed384b243e2a802f
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author_id_fullname_str_mv ccd66b64d11d76b9cd8b28e9d42a0ff0_***_Thomas Reitmaier
6d662d9e2151b302ed384b243e2a802f_***_Jen Pearson
10b46d7843c2ba53d116ca2ed9abb56e_***_Matt Jones
cb3b57a21fa4e48ec633d6ba46455e91_***_Simon Robinson
author Thomas Reitmaier
Jen Pearson
Matt Jones
Simon Robinson
author2 Thomas Reitmaier
Electra Wallington
Ondrej Klejch
Nina Markl
Léa-Marie Lam-Yee-Mui
Jen Pearson
Matt Jones
Peter Bell
Simon Robinson
format Conference Paper/Proceeding/Abstract
container_title ACM CHI Conference on Human Factors in Computing Systems: CHI' 23
container_start_page 1
publishDate 2023
institution Swansea University
isbn 978-1-4503-9421-5/23/04
doi_str_mv 10.1145/3544548.3581385
publisher ACM
college_str Faculty of Science and Engineering
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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
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description In this paper we develop approaches to automatic speech recognition (ASR) development that suit the needs and functions of underheard language speakers. Our novel contribution to HCI is to show how community-engagement can surface key technical and social issues and opportunities for more efective speech-based systems. We introduce a bespoke toolkit of technologies and showcase how we utilised the toolkit to engage communities of under-heard language speakers; and, through that engagement process, situate key aspects of ASR development in community contexts. The toolkit consists of (1) an information appliance to facilitate spoken-data collection on topics of community interest, (2) a mobile app to create crowdsourced transcripts of collected data, and (3) demonstrator systems to showcase ASR capabilities and to feed back research results to community members. Drawing on the sensibilities we cultivated through this research, we present a series of challenges to the orthodoxy of state-of-the-art approaches to ASR development.
published_date 2023-04-23T05:22:55Z
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score 11.04748

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