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

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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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