Decolonising Speech and Language Technology

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review

    93 Citations (Scopus)
    332 Downloads (Pure)

    Abstract

    After generations of exploitation, Indigenous people often respond negatively to the idea that their languages are data ready for the taking. By treating Indigenous knowledge as a commodity, speech and language technologists risk disenfranchising local knowledge authorities, reenacting the causes of language endangerment. Scholars in related fields have responded to calls for decolonisation, and we in the speech and language technology community need to follow suit, and explore what this means for our practices that involve Indigenous languages and the communities who own them. This paper reviews colonising discourses in speech and language technology, and suggests new ways of working with Indigenous communities, and seeks to open a discussion of a postcolonial approach to computational methods for supporting language vitality.

    Original languageEnglish
    Title of host publicationCOLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference
    EditorsDonia Scott, Nuria Bel, Chengqing Zong
    Place of PublicationCzech Republic
    PublisherAssociation for Computational Linguistics (ACL)
    Pages3504-3519
    Number of pages16
    Edition1
    ISBN (Electronic)9781952148279
    DOIs
    Publication statusPublished - 2020
    Event28th International Conference on Computational Linguistics, COLING 2020 - Virtual, Online, Spain
    Duration: 8 Dec 202013 Dec 2020

    Publication series

    NameCOLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference

    Conference

    Conference28th International Conference on Computational Linguistics, COLING 2020
    Country/TerritorySpain
    CityVirtual, Online
    Period8/12/2013/12/20

    Bibliographical note

    Funding Information:
    I am indebted to the Bininj people of Northern Australia for the opportunity to live and work in their community, and particularly to Lois Nadjamerrek, Stuart Guymala, and Dean Yibarbuk for their friendship and guidance over many years. This paper has benefitted from feedback from Mat Bettinson, William Lane, Jennyfer Lawrence Taylor, Brandon Wiltshire, and several anonymous reviewers. This research has been supported by grants from the Australian Research Council entitled Learning English and Aboriginal Languages for Work, and the Indigenous Languages and Arts Program entitled Mobile Software for Oral Language Learning in Arnhem Land, and covered by a research permit from the Northern Land Council and approvals from the board of Warddeken Land Management and the CDU Human Research Ethics Committee.

    Publisher Copyright:
    © 2020 COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference. All rights reserved.

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