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Anuoluwapo Aremu

11 accepted papers

2025

Does Generative AI speak Nigerian-Pidgin?: Issues about Representativeness and Bias for Multilingualism in LLMs

NAACL 2025findings

Nigeria is a multilingual country with 500+ languages. Naija is a Nigerian Pidgin spoken by approximately 120M speakers and it is a mixed language (e.g., English, Portuguese, Yoruba, Hausa and Igbo). Although it has mainly been a spoken language until recently, there are some online platforms (e.g.,…

2025

The Esethu Framework: Reimagining Sustainable Dataset Governance and Curation for Low-Resource Languages

ACL 2025long

This paper presents the Esethu Framework, a sustainable data curation framework specifically designed to empower local communities and ensure equitable benefit-sharing from their linguistic resource. This framework is supported by the Esethu license, a novel community-centric data license. As a proo…

Cited by 0SourcePDFScholar
2024

AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages

NAACL 2024long

Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as BLEU, which typically show a weaker correlation wi…

2024

Mitigating Translationese in Low-resource Languages: The Storyboard Approach

COLING 2024main

Low-resource languages often face challenges in acquiring high-quality language data due to the reliance on translation-based methods, which can introduce the translationese effect. This phenomenon results in translated sentences that lack fluency and naturalness in the target language. In this pape…

Cited by 2SourcePDFScholar
2024

Voices Unheard: NLP Resources and Models for Yorùbá Regional Dialects

EMNLP 2024main

Yoruba—an African language with roughly 47 million speakers—encompasses a continuum with several dialects. Recent efforts to develop NLP technologies for African languages have focused on their standard dialects, resulting in disparities for dialects and varieties for which there are little to no re…

2024

ÌròyìnSpeech: A Multi-purpose Yorùbá Speech Corpus

COLING 2024main

We introduce ÌròyìnSpeech corpus—a new dataset influenced by a desire to increase the amount of high quality, freely available, contemporary Yorùbá speech data that can be used for both Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) tasks. We curated about 23,000 text sentences from the…

2023

Cross-lingual Open-Retrieval Question Answering for African Languages

EMNLP 2023long findings

African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems -- those that retrieve answer content from other languages while s…

Cited by 0SourceScholar
2023

MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African languages

ACL 2023long

In this paper, we present AfricaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages. We discuss the challenges in annotating POS for these languages using the universal dependencies (UD) guidelines. We conducted extensive POS baseline experiments using both c…

2023

Multi-lingual and Multi-cultural Figurative Language Understanding

ACL 2023findings

Figurative language permeates human communication, but at the same time is relatively understudied in NLP. Datasets have been created in English to accelerate progress towards measuring and improving figurative language processing in language models (LMs). However, the use of figurative language is…

Cited by 26SourcePDFScholar
2022

A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation

NAACL 2022long

Recent advances in the pre-training for language models leverage large-scale datasets to create multilingual models. However, low-resource languages are mostly left out in these datasets. This is primarily because many widely spoken languages that are not well represented on the web and therefore ex…

2022

MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition

EMNLP 2022main

African languages are spoken by over a billion people, but they are under-represented in NLP research and development. Multiple challenges exist, including the limited availability of annotated training and evaluation datasets as well as the lack of understanding of which settings, languages, and re…