A computational model for interactive transcription

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


    Transcribing low resource languages can be challenging in the absence of a good lexicon and trained transcribers. Accordingly, we seek a way to enable interactive transcription whereby the machine amplifies human efforts. This paper presents a data model and a system architecture for interactive transcription, supporting multiple modes of interactivity, increasing the likelihood of finding tasks that engage local participation in language work. The approach also supports other applications which are useful in our context, including spoken document retrieval and language learning.
    Original languageEnglish
    Title of host publicationProceedings of the Second Workshop on Data Science with Human-in-the-Loop
    Subtitle of host publicationLanguage Advances
    EditorsEduard Dragut, Yunyao Li, Lucian Popa, Slobodan Vucetic
    Place of PublicationUSA
    PublisherAssociation for Computational Linguistics (ACL)
    Number of pages7
    ISBN (Print)9781954085398
    Publication statusPublished - Jun 2021
    EventThe 2nd Workshop on Data Science with Human-in-the-loop: Language Advances - Virtual
    Duration: 11 Jun 202111 Jun 2021


    WorkshopThe 2nd Workshop on Data Science with Human-in-the-loop
    Abbreviated titleDaSH-LA 2021


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