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Supporting SENĆOŦEN language documentation efforts with Automatic Speech Recognition

From National Research Council Canada

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Linkhttps://aclanthology.org/2025.computel-main.4/
AuthorSearch for: 1; Search for: 1ORCID identifier: https://orcid.org/0000-0002-7173-0225; Search for: 1ORCID identifier: https://orcid.org/0000-0001-6552-5324; Search for: ; Search for: 1ORCID identifier: https://orcid.org/0009-0009-1413-2892; Search for: 1
Affiliation
  1. National Research Council Canada. Digital Technologies
FormatText, Article
ConferenceEight Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL 2025), March 4-5, 2025, Honolulu, Hawai'i, United States
Abstract
The SENĆOŦEN language, spoken on the Saanich peninsula of southern Vancouver Island, is in the midst of vigorous language revitalization efforts to turn the tide of language loss as a result of colonial language policies. To support these on-the-ground efforts, the community is turning to digital technology. Automatic Speech Recognition (ASR) technology holds great promise for accelerating language documentation and the creation of educational resources. However, developing ASR systems for SENCOTEN is challenging due to limited data and significant vocabulary variation from its polysynthetic structure and stress-driven metathesis. To address these challenges, we propose an ASR-driven documentation pipeline that leverages augmented speech data from a text-to-speech (TTS) system and cross-lingual transfer learning with Speech Foundation Models (SFMs). An n-gram language model is also incorporated via shallow fusion or n-best restoring to maximize the use of available data. Experiments on the SENCOTEN dataset show aword error rate (WER) of 19.34% and a character error rate (CER) of 5.09% on the test set with a 57.02% out-of-vocabulary (OOV) rate. After filtering minor cedilla-related errors, WER improves to 14.32% (26.48% on unseen words) and CER to 3.45%, demonstrating the potential of our ASR-driven pipeline to support SENCOTEN language documentation.
Publication date
PublisherAssociation for Computational Linguistics
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  • Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages, 2025.computel-main.4 (March 2025): 29–39.
LanguageEnglish
Peer reviewedYes
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Record identifier69bc601c-843b-4d94-8622-411b0b59cdd6
Record created2025-07-31
Record modified2025-12-07
Date modified: