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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In this paper we develop approaches to automatic speech recognition (ASR) development that suit the needs and functions of under-heard language speakers. Our novel contribution to HCI is to show how community-engagement can surface key technical and social issues and opportunities for more effective 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 crowd sourced 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
Original languageEnglish
Title of host publicationCHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York
PublisherACM
Pages1-17
Number of pages17
ISBN (Print)9781450394215
DOIs
Publication statusPublished - 19 Apr 2023
EventACM CHI 2023 Conference on Human Factors in Computing Systems - Hamburg, Germany
Duration: 23 Apr 202328 Apr 2023
https://chi2023.acm.org/

Conference

ConferenceACM CHI 2023 Conference on Human Factors in Computing Systems
Abbreviated titleCHI'23
Country/TerritoryGermany
CityHamburg
Period23/04/2328/04/23
Internet address

Keywords / Materials (for Non-textual outputs)

  • text/speech/language
  • automatic speech recognition
  • mobile devices: phones/tablets

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