Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges

TL;DR

This paper presents a framework for applying Generative AI and Large Language Models to language preservation, emphasizing community governance, ethical safeguards, and practical evaluation, demonstrated through the revitalization of Te Reo Māori.

Contribution

It introduces a novel analytical framework for evaluating GenAI applications in language preservation, integrating community needs and ethical considerations, with practical validation on Te Reo Māori.

Findings

Achieved 92% accuracy in community-led speech recognition

Identified challenges in data sovereignty and model bias

Demonstrated the framework's effectiveness in real-world revitalization efforts

Abstract

The global crisis of language endangerment meets a technological turning point as Generative AI (GenAI) and Large Language Models (LLMs) unlock new frontiers in automating corpus creation, transcription, translation, and tutoring. However, this promise is imperiled by fragmented practices and the critical lack of a methodology to navigate the fraught balance between LLM capabilities and the profound risks of data scarcity, cultural misappropriation, and ethical missteps. This paper introduces a novel analytical framework that systematically evaluates GenAI applications against language-specific needs, embedding community governance and ethical safeguards as foundational pillars. We demonstrate its efficacy through the Te Reo M\=aori revitalization, where it illuminates successes, such as community-led Automatic Speech Recognition achieving 92% accuracy, while critically surfacing persistent challenges in data sovereignty and model bias for digital archives and educational tools. Our findings underscore that GenAI can indeed revolutionize language preservation, but only when interventions are rigorously anchored in community-centric data stewardship, continuous evaluation, and transparent risk management. Ultimately, this framework provides an indispensable toolkit for researchers, language communities, and policymakers, aiming to catalyze the ethical and high-impact deployment of LLMs to safeguard the world's linguistic heritage.