AI MEETS TRADITION: INNOVATIVE SOLUTIONS FOR SAVING ENDANGERED LANGUAGES AND ORAL HERITAGE

Abstract

Endangered language is the maintenance of historical tradition, oral customs and ancestors' wisdom. The decreasing number of languages has been heightened by urban expansion, the rise of globalization and limited multigenerational distribution, by the end of the era.  It is estimated that approximately forty percent of the world's languages would have extinct. This study explores how offline technologies and artificial intelligence (AI) can be utilized to digitally preserve endangered languages and oral traditions. The CARE concepts (Collective advantages Authority to exercise control, Responsibility, or accountability, Ethics) and OCAP® (Ownership, Management, Access, and Presence) are both instances of cultural data management principles that are mentioned. Applying the qualitative method, data collected from technology experts, community leaders, and language representatives via in-depth interviews and field observations. Studies show that although offline programs fill association gaps in remote regions, AI tools specifically ASR (Automated Speech Recognition) and Natural Language Processing (NLP) offer significant potential for language translation, transcription, and their preservation. However, challenges including bias in AI models, an inadequate amount of resources, and cultural awareness in processing data seem to be major considerations. The study indicates how significant community-led preservation approaches, moral AI design, and offline tool implementation are to overall language documentation. This study offers a framework for the technologically achievable as well as cultural appropriate preservation of language diversity by integrating technical innovation with indigenous management principles.