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arXiv:2405.06818v2 Announce Type: replace Abstract: Natural Language Processing (NLP) for Ghana's 73 living indigenous languages remains deeply fragmented, under-resourced, and heavily skewed toward...
The paper surveys NLP research on Nigeria’s three major low‑resource languages—Hausa, Yoruba, and Igbo—covering over 500 languages spoken by 175 million people. It reviews 293 studies, finding that only 27.6% produced new linguistic resources, indicating a heavy reliance on repurposing existing data. The authors highlight under‑explored challenges such as morphological analysis and diacritic representation, and call for collaborative resource enrichment and community support to advance NaijaNLP and low‑resource NLP more broadly.
arXiv:2610.28173v1 Announce Type: cross Abstract: Large Language Models (LLMs) depend fundamentally on the diversity, depth, and factual rigor of their pre-training corpora. However, contemporary fou...
arXiv:2606. 12708v1 Announce Type: cross Abstract: Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP.
arXiv:2610.27269v1 Announce Type: new Abstract: With the widespread adoption of large language models (LLMs) across languages and domains, AI safety has emerged as a critical global concern. However,...
The paper analyzes the distribution of artificial intelligence resources across 6,003 languages, revealing that a small number of languages dominate and that disparities are widening exponentially. It compares the diffusion of AI with earlier information technologies, noting a hype-driven spread pattern. The authors introduce the Language AI Readiness Index (EQUATE) to map technological, socio-economic, and infrastructural prerequisites for AI deployment, aiming to guide equitable diffusion of language AI.