Learning Through Transcription

Mat Bettinson, Steven Bird

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

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    Abstract

    Transcribing speech for primarily oral, local languages is often a joint effort involving speakers and outsiders. It is commonly motivated by externally-defined scientific goals, alongside local motivations such as language acquisition and access to heritage materials. We explore the task of 'learning through transcription' through the design of a system for collaborative speech annotation. We have developed a prototype to support local and remote learner-speaker interactions in remote Aboriginal communities in northern Australia. We show that situated systems design for inclusive non-expert practice is a promising new direction for working with speakers of local languages.

    Original languageEnglish
    Title of host publicationProceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages
    EditorsSarah Moeller, Antonios Anastasopoulos, Antti Arppe, Aditi Chaudhary, Atticus Harrigan, Josh Holden, Jordan Lachler, Alexis Palmer, Shruti Rijhwani, Lane Schwartz
    Place of PublicationPennsylvania
    PublisherAssociation for Computational Linguistics (ACL)
    Pages83-92
    Number of pages10
    Edition1
    ISBN (Electronic)9781955917308
    DOIs
    Publication statusPublished - May 2022
    Event5th Workshop on the Use of Computational Methods in the Study of Endangered Languages, COMPUTEL 2022 - Dublin, Ireland
    Duration: 26 May 202227 May 2022
    Conference number: 5

    Publication series

    NameCOMPUTEL 2022 - 5th Workshop on the Use of Computational Methods in the Study of Endangered Languages, Proceedings of the Workshop

    Conference

    Conference5th Workshop on the Use of Computational Methods in the Study of Endangered Languages, COMPUTEL 2022
    Abbreviated titleComputEL 2022
    Country/TerritoryIreland
    CityDublin
    Period26/05/2227/05/22

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