Artificial Intelligence and Indigenous Language Revitalization: A Gadé Language Digitization Model

Abstract

The marginalization of low-resource indigenous languages within contemporary Artificial Intelligence (AI) and Natural Language Processing (NLP) ecosystems poses a significant threat to global linguistic diversity and cultural heritage preservation. This study presents a comprehensive AI-driven Gadé Language Digitization Model designed to support the revitalization, preservation, and technological integration of the Gadé language of North-Central Nigeria. As a tone-rich Niger-Congo language characterized by complex morphosyntactic structures, nuanced semantic expressions, and an indigenous philosophical framework rooted in Gaboism, Gadé presents substantial challenges to conventional Large Language Models (LLMs), which often fail to adequately represent tonal distinctions and culturally embedded meanings. To address these limitations, the study proposes an integrated computational framework
incorporating a Tone-Aware Automatic Speech Recognition (ASR) system that maps fundamental frequency (f0) contours to native orthographic markers, alongside a Neural Machine Translation (NMT) architecture enhanced by custom subword tokenization optimized for Niger-Congo linguistic patterns. Guided by principles of community-led data sovereignty, linguistic authenticity, and ethical AI development, the model utilizes a high-quality annotated corpus developed collaboratively with native speakers, community elders, and the Institute of Gade and Classical Studies. Experimental evaluations indicate notable reductions in Word Error Rate (WER) and significant improvements in translation quality and semantic preservation when compared with baseline multilingual models. Beyond technological innovation, the proposed framework establishes a scalable digital repository, educational infrastructure, and language technology ecosystem for Gadé. The study demonstrates how AI can serve as a transformative instrument for indigenous language revitalization and provides a replicable blueprint for preserving endangered African languages in the digital age.