# Developing a Mixed-Methods Pipeline for Community-Oriented Digitization of Kwak'wala Legacy Texts

arXiv: https://arxiv.org/abs/2506.01775 · HTML: https://mlsanity.com/paper/2506.01775/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 30 references that are in the map.
- First posted on arXiv 2 Jun 2025.

## Builds on (most cited first, 10 of 10)

- [Bag of Tricks for Efficient Text Classification](https://mlsanity.com/paper/1607.01759/) (2016)
- [Nougat: Neural Optical Understanding for Academic Documents](https://mlsanity.com/paper/2308.13418/) (2023)
- [A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://mlsanity.com/paper/2010.12309/) (2020)
- [Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)](https://mlsanity.com/paper/2001.00139/) (2020)
- [OCR Post Correction for Endangered Language Texts](https://mlsanity.com/paper/2011.05402/) (2020)
- [Sequence-to-Label Script Identification for Multilingual OCR](https://mlsanity.com/paper/1708.04671/) (2017)
- [Lexically Aware Semi-Supervised Learning for OCR Post-Correction](https://mlsanity.com/paper/2111.02622/) (2021)
- [LIMIT: Language Identification, Misidentification, and Translation using Hierarchical Models in 350+ Languages](https://mlsanity.com/paper/2305.14263/) (2023)
- [User-Centric Evaluation of OCR Systems for Kwak'wala](https://mlsanity.com/paper/2302.13410/) (2023)
- [LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books](https://mlsanity.com/paper/1701.07396/) (2017)

## Abstract (arXiv)

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.