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Main Authors: Agarwal, Milind, Rosenblum, Daisy, Anastasopoulos, Antonios
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2506.01775
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author Agarwal, Milind
Rosenblum, Daisy
Anastasopoulos, Antonios
author_facet Agarwal, Milind
Rosenblum, Daisy
Anastasopoulos, Antonios
contents Kwak'wala is an Indigenous language spoken in British Columbia, with a rich legacy of published documentation spanning more than a century, and an active community of speakers, teachers, and learners engaged in language revitalization. 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 digitization through optical character recognition has the potential to facilitate transliteration into modern orthographies and the creation of other language technologies. In this paper, we apply 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 produce a final high-quality transcription.
format Preprint
id arxiv_https___arxiv_org_abs_2506_01775
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak'wala Legacy Texts
Agarwal, Milind
Rosenblum, Daisy
Anastasopoulos, Antonios
Computation and Language
Kwak'wala is an Indigenous language spoken in British Columbia, with a rich legacy of published documentation spanning more than a century, and an active community of speakers, teachers, and learners engaged in language revitalization. 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 digitization through optical character recognition has the potential to facilitate transliteration into modern orthographies and the creation of other language technologies. In this paper, we apply 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 produce a final high-quality transcription.
title Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak'wala Legacy Texts
topic Computation and Language
url https://arxiv.org/abs/2506.01775