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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