NüshuRescue: Reviving the Endangered Nüshu Language with AI

Researchers Ivory Yang, Weicheng Ma, and Soroush Vosoughi presented NüshuRescue, an AI-driven framework for training large language models on endangered languages with minimal data, at COLING 2025 in Abu Dhabi. Using GPT-4-Turbo with no prior exposure to Nüshu and only 35 short examples from NCGold, a new 500-sentence Nüshu-Chinese parallel corpus, NüshuRescue reached 48.69% translation accuracy on 50 withheld sentences and generated NCSilver, 98 newly translated modern Chinese sentences. The team also built FastText-based and Seq2Seq models and released all datasets and code publicly on GitHub.

Abstract The preservation and revitalization of endangered and extinct languages is a meaningful endeavor, conserving cultural heritage while enriching fields like linguistics and anthropology. However, these languages are typically low-resource, making their reconstruction labor-intensive and costly. This challenge is exemplified by Nüshu, a rare script historically used by Yao women in China for self-expression within a patriarchal society. To address this challenge, we introduce NüshuRescue, an AI-driven framework designed to train large language models LLMs on endangered languages with minimal data. NüshuRescue automates evaluation and expands target corpora to accelerate linguistic revitalization. As a foundational component, we developed NCGold, a 500-sentence Nüshu-Chinese parallel corpus, the first publicly available dataset of its kind. Leveraging GPT-4-Turbo, with no prior exposure to Nüshu and only 35 short examples from NCGold, NüshuRescue achieved 48.69% translation accuracy on 50 withheld sentences and generated NCSilver, a set of 98 newly translated modern Chinese sentences of varying lengths. In addition, we developed FastText-based and Seq2Seq models to further support research on Nüshu. NüshuRescue provides a versatile and scalable tool for the revitalization of endangered languages, minimizing the need for extensive human input. All datasets and code have been made publicly available at https://github.com/ivoryayang/NushuRescue https://github.com/ivoryayang/NushuRescue . - Anthology ID: - 2025.coling-main.468 - Volume: - Proceedings of the 31st International Conference on Computational Linguistics /volumes/2025.coling-main/ - Month: - January - Year: - 2025 - Address: - Abu Dhabi, UAE - Editors: - Owen Rambow /people/owen-rambow/ , Leo Wanner /people/leo-wanner/ , Marianna Apidianaki /people/marianna-apidianaki/ , Hend Al-Khalifa /people/hend-al-khalifa/ , Barbara Di Eugenio /people/barbara-di-eugenio/ , Steven Schockaert /people/steven-schockaert/ - Venue: - COLING /venues/coling/ - SIG: - Publisher: - Association for Computational Linguistics - Note: - Pages: - 7020–7034 - Language: - URL: - https://aclanthology.org/2025.coling-main.468/ https://aclanthology.org/2025.coling-main.468/ - DOI: - Cite ACL : - Ivory Yang, Weicheng Ma, and Soroush Vosoughi. 2025. NüshuRescue: Reviving the Endangered Nüshu Language with AI https://aclanthology.org/2025.coling-main.468/ . In Proceedings of the 31st International Conference on Computational Linguistics , pages 7020–7034, Abu Dhabi, UAE. Association for Computational Linguistics. - Cite Informal : - NüshuRescue: Reviving the Endangered Nüshu Language with AI https://aclanthology.org/2025.coling-main.468/ Yang et al., COLING 2025 - PDF: - https://aclanthology.org/2025.coling-main.468.pdf https://aclanthology.org/2025.coling-main.468.pdf