A Computational Model for Interactive Transcription

William Abbott Lane, Mat Bettinson, Steven Bird

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

    12 Downloads (Pure)

    Abstract

    Transcribing low resource languages can be challenging in the absence of a comprehensive lexicon and proficient transcribers. Accordingly, we seek a way to enable interactive transcription, whereby the machine amplifies human efforts. This paper presents a computational model for interactive transcription, supporting multiple modes of interactivity and increasing the likelihood of finding tasks that stimulate local participation. The approach also supports other applications which are useful in low resource contexts, including spoken document retrieval and language learning.

    Original languageEnglish
    Title of host publicationDaSH-LA 2021 - 2nd Workshop on Data Science with Human-in-the-Loop
    Subtitle of host publicationLanguage Advances, Proceedings
    EditorsEduard Dragut, Yunyao Li, Lucian Popa, Slobodan Vucetic
    Place of PublicationUSA
    PublisherAssociation for Computational Linguistics (ACL)
    Pages105-111
    Number of pages7
    Edition1
    ISBN (Electronic)9781954085398
    Publication statusPublished - Jun 2021
    Event2nd Workshop on Data Science with Human-in-the-Loop: Language Advances, DaSH-LA 2021 - Virtual, Online
    Duration: 11 Jun 2021 → …

    Publication series

    NameDaSH-LA 2021 - 2nd Workshop on Data Science with Human-in-the-Loop: Language Advances, Proceedings

    Conference

    Conference2nd Workshop on Data Science with Human-in-the-Loop: Language Advances, DaSH-LA 2021
    CityVirtual, Online
    Period11/06/21 → …

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