Ibom NLP: A Step Toward Inclusive Natural Language Processing for Nigeria's Minority Languages

TL;DR

Ibom NLP introduces Ibom-MT and Ibom-TC to extend Flores-200 and SIB-200 to four Akwa Ibom minority languages (Anaang, Efik, Ibibio, Oro), addressing data scarcity in Nigeria's linguistic diversity. The work evaluates MT and TC through fine-tuning of encoder-decoder models and a range of LLM prompting approaches, revealing strong zero-shot MT limitations but notable gains from 2-stage fine-tuning and few-shot TC prompts. A key finding is that African-centric encoders outperform general multilingual models for TC, while few-shot Gemini prompts can substantially boost TC results and partially close MT gaps, though MT metric agreement remains imperfect. The datasets and evaluation protocols provide resources to advance NLP for minority Nigerian languages and motivate broader data collection and model development beyond the top languages in Africa.

Abstract

Nigeria is the most populous country in Africa with a population of more than 200 million people. More than 500 languages are spoken in Nigeria and it is one of the most linguistically diverse countries in the world. Despite this, natural language processing (NLP) research has mostly focused on the following four languages: Hausa, Igbo, Nigerian-Pidgin, and Yoruba (i.e <1% of the languages spoken in Nigeria). This is in part due to the unavailability of textual data in these languages to train and apply NLP algorithms. In this work, we introduce ibom -- a dataset for machine translation and topic classification in four Coastal Nigerian languages from the Akwa Ibom State region: Anaang, Efik, Ibibio, and Oro. These languages are not represented in Google Translate or in major benchmarks such as Flores-200 or SIB-200. We focus on extending Flores-200 benchmark to these languages, and further align the translated texts with topic labels based on SIB-200 classification dataset. Our evaluation shows that current LLMs perform poorly on machine translation for these languages in both zero-and-few shot settings. However, we find the few-shot samples to steadily improve topic classification with more shots.

Figures (1)

• Figure 1: Map showing the regions where the IBOM languages are spoken in Nigeria including Anaang, Efik, Ibibo, and Oro. The languages are native to the South-South region of Nigeria, primarily spoken in the Akwa-Ibom state painted in Green.