Towards Building an Automatic Transcription System for Language Documentation: Experiences from Muyu

Alexander Zahrer, Andrej Žgank , Barbara Schuppler

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

Since at least half of the world’s 6000 plus languages will vanish during the 21st century, language documentation has become a rapidly growing field in linguistics. A fundamental challenge for language documentation is the ”transcription bottleneck”. Speech technology may deliver the decisive breakthrough for overcoming the transcription bottleneck. This paper presents first experiments from the development of ASR4LD, a new automatic speech recognition (ASR) based tool for language documentation (LD). The experiments are based on recordings from an ongoing documentation project for the endangered Muyu language in New Guinea. We compare phoneme recognition experiments with American English, Austrian German and Slovenian as source language and Muyu as target language. The Slovenian acoustic models achieve the by far best performance (43.71% PER) in comparison to 57.14% PER with American English, and 89.49% PER with Austrian German. Whereas part of the errors can be explained by phonetic variation, the recording mismatch poses a major problem. On the long term, ASR4LD will not only be an integral part of the ongoing documentation project of Muyu, but will be further developed in order to facilitate also the language documentation process of other language groups
Originalspracheenglisch
TitelLREC 2020 Conference Proceedings
Herausgeber (Verlag)European Language Resources Association
Seiten2886 ‑ 2893
ISBN (elektronisch)979-10-95546-34-4
PublikationsstatusVeröffentlicht - 2020
VeranstaltungLREC 2020: 12th International Conference on Language Resources and Evaluation - Virtuell, Frankreich
Dauer: 11 Mai 202016 Mai 2020

Konferenz

KonferenzLREC 2020
LandFrankreich
OrtVirtuell
Zeitraum11/05/2016/05/20

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  • Dieses zitieren

    Zahrer, A., Žgank , A., & Schuppler, B. (2020). Towards Building an Automatic Transcription System for Language Documentation: Experiences from Muyu. in LREC 2020 Conference Proceedings (S. 2886 ‑ 2893). European Language Resources Association.