Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/24793

Integrating Automatic Transcription into the Language Documentation Workflow: Experiments with Na Data and the Persephone Toolkit

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Title:Integrating Automatic Transcription into the Language Documentation Workflow: Experiments with Na Data and the Persephone Toolkit
Authors:Michaud, Alexis
Adams, Oliver
Cohn, Trevor Anthony
Neubig, Graham
Guillaume, Séverine
Keywords:language documentation
automatic speech transcription
automatic speech recognition
natural language processing
endangered languages
show 5 moresound archive
multimedia corpora
interdisciplinarity
open-source software
open access
show less
Date Issued:Sep 2018
Publisher:University of Hawaii Press
Citation:Michaud, Alexis, Oliver Adams, Trevor Anthony Cohn, Graham Neubig & Séverine Guillaume. 2018. Integrating Automatic Transcription into the Language Documentation Workflow: Experiments with Na Data and the Persephone Toolkit. Language Documentation & Conservation 12. 393-429.
Abstract:Automatic speech recognition tools have potential for facilitating language documentation, but in practice these tools remain little-used by linguists for a variety of reasons, such as that the technology is still new (and evolving rapidly), user-friendly interfaces are still under development, and case studies demonstrating the practical usefulness of automatic recognition in a low-resource setting remain few. This article reports on a success story in integrating automatic transcription into the language documentation workflow, specifically for Yongning Na, a language of Southwest China. Using Persephone, an open-source toolkit, a single-speaker speech transcription tool was trained over five hours of manually transcribed speech. The experiments found that this method can achieve a remarkably low error rate (on the order of 17%), and that automatic transcriptions were useful as a canvas for the linguist. The present report is intended for linguists with little or no knowledge of speech processing. It aims to provide insights into (i) the way the tool operates and (ii) the process of collaborating with natural language processing specialists. Practical recommendations are offered on how to anticipate the requirements of this type of technology from the early stages of data collection in the field.
Pages/Duration:37 pages
URI/DOI:http://hdl.handle.net/10125/24793
ISSN:1934-5275
Rights:Creative Commons Attribution-NonCommercial 4.0 International
Attribution-NonCommercial 3.0 United States
http://creativecommons.org/licenses/by-nc/3.0/us/
Appears in Collections: Volume 12 : Language Documentation & Conservation


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