NaijaNLP: A Survey of Nigerian Low-Resource Languages

TL;DR

This paper provides the first comprehensive review of NLP research for Nigeria's three major low-resource languages, highlighting resource gaps, challenges, and future directions for advancing language understanding and generation.

Contribution

It offers a detailed assessment of linguistic resources and challenges in Hausa, Yoruba, and Igbo, emphasizing the need for resource development and collaborative efforts.

Findings

Only 25.1% of studies contribute new linguistic resources

Diacritics representation remains under-explored

Significant resource gaps hinder NLP progress

Abstract

With over 500 languages in Nigeria, three languages -- Hausa, Yor\`ub\'a and Igbo -- spoken by over 175 million people, account for about 60% of the spoken languages. However, these languages are categorised as low-resource due to insufficient resources to support tasks in computational linguistics. Several research efforts and initiatives have been presented, however, a coherent understanding of the state of Natural Language Processing (NLP) - from grammatical formalisation to linguistic resources that support complex tasks such as language understanding and generation is lacking. This study presents the first comprehensive review of advancements in low-resource NLP (LR-NLP) research across the three major Nigerian languages (NaijaNLP). We quantitatively assess the available linguistic resources and identify key challenges. Although a growing body of literature addresses various NLP downstream tasks in Hausa, Igbo, and Yor\`ub\'a, only about 25.1% of the reviewed studies contribute new linguistic resources. This finding highlights a persistent reliance on repurposing existing data rather than generating novel, high-quality resources. Additionally, language-specific challenges, such as the accurate representation of diacritics, remain under-explored. To advance NaijaNLP and LR-NLP more broadly, we emphasise the need for intensified efforts in resource enrichment, comprehensive annotation, and the development of open collaborative initiatives.