AI-Powered Innovations for Documenting and Revitalizing African Languages

Abstract

The documentation and revitalization of African languages are crucial for preserving the continent’s linguistic and cultural heritage amid increasing threats of language endangerment. This study presents a systematic review of existing literature on artificial intelligence (AI)-driven approaches to language documentation and revitalization, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data were collected from twenty academic digital repositories and peer-reviewed journals specializing in computational linguistics, AI applications in language preservation, and African linguistics. Four major databases were specifically searched: Google Scholar, SpringerLink, ScienceDirect, and African Journals Online (AJOL). Peer-reviewed articles from established repositories were analyzed to explore key AI applications such as speech recognition, machine learning for transcription, neural machine translation, and digital archiving. The findings reveal that AI significantly enhances language preservation by enabling automated transcription, corpus development, and the creation of interactive learning tools. Nonetheless, challenges remain, including limited data availability, ethical concerns over language ownership, and technological accessibility in marginalized communities, which hinder widespread implementation. The study emphasizes the importance of interdisciplinary collaboration among linguists, AI developers, and local communities to ensure culturally sensitive and effective AI solutions. Ultimately, this review highlights the transformative potential of AI in supporting the sustainable revitalization of indigenous African languages and contributing to global linguistic resilience.

Keywords

References

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