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    <abstract>Kwak’wala is an Indigenous language spoken in British Columbia, with a rich legacy of pub- lished documentation spanning more than a century, and an active community of speakers, teachers, and learners engaged in language revi- talization. Over 11 volumes of the earliest texts created during the collaboration between Franz Boas and George Hunt have been scanned but remain unreadable by machines. Complete dig- itization through optical character recognition has the potential to facilitate transliteration into modern orthographies and the creation of other language technologies. In this paper, we ap- ply the latest OCR techniques to a series of Kwak’wala texts only accessible as images, and discuss the challenges and unique adaptations necessary to make such technologies work for these real-world texts. Building on previous methods, we propose using a mix of off-the- shelf OCR methods, language identification, and masking to effectively isolate Kwak’wala text, along with post-correction models, to pro- duce a final high-quality transcription.</abstract>
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%0 Conference Proceedings
%T Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak’wala Legacy Texts
%A Agarwal, Milind
%A Anastasopoulos, Antonios
%A Rosenblum, Daisy
%Y Lachler, Jordan
%Y Agyapong, Godfred
%Y Arppe, Antti
%Y Moeller, Sarah
%Y Chaudhary, Aditi
%Y Rijhwani, Shruti
%Y Rosenblum, Daisy
%S Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages
%D 2025
%8 March
%I Association for Computational Linguistics
%C Honolulu, Hawaii, USA
%F agarwal-etal-2025-developing
%X Kwak’wala is an Indigenous language spoken in British Columbia, with a rich legacy of pub- lished documentation spanning more than a century, and an active community of speakers, teachers, and learners engaged in language revi- talization. Over 11 volumes of the earliest texts created during the collaboration between Franz Boas and George Hunt have been scanned but remain unreadable by machines. Complete dig- itization through optical character recognition has the potential to facilitate transliteration into modern orthographies and the creation of other language technologies. In this paper, we ap- ply the latest OCR techniques to a series of Kwak’wala texts only accessible as images, and discuss the challenges and unique adaptations necessary to make such technologies work for these real-world texts. Building on previous methods, we propose using a mix of off-the- shelf OCR methods, language identification, and masking to effectively isolate Kwak’wala text, along with post-correction models, to pro- duce a final high-quality transcription.
%U https://aclanthology.org/2025.computel-main.15/
%P 133-138

Markdown (Informal)

[Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak’wala Legacy Texts](https://aclanthology.org/2025.computel-main.15/) (Agarwal et al., ComputEL 2025)

• Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak’wala Legacy Texts (Agarwal et al., ComputEL 2025)

ACL

• Milind Agarwal, Antonios Anastasopoulos, and Daisy Rosenblum. 2025. Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak’wala Legacy Texts. In Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages, pages 133–138, Honolulu, Hawaii, USA. Association for Computational Linguistics.