177 citations · 547 across the 80 of their papers we have counts for
79 papers · 1 filter
Title Redacted
Sangmin Lee, Yejin Jeon, David Ifeoluwa Adelani
arXiv admin note: This version has been removed by arXiv administrators as the submitter did not have the rights to agree to the license at the time of submission
The ÌròyìnSpeech Text Corpus: 24,905 Curated Yorùbá Sentences for Speech and Language Technology
Kola Tubosun, Anuoluwapo Aremu, Aanuoluwapo Aremu +3
ÌròyìnSpeech is a 42-hour, 80-speaker Yorùbá read-speech corpus whose audio has been distributed by ELRA since 2024. This paper describes the release of its text component: 24,905…
OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languages
David Guzmán, Luel Hagos Beyene, Jesujoba Oluwadara Alabi +3
Recent advances in neural text-to-speech (TTS) and multilingual speech generation have substantially improved synthetic speech quality, yet these gains remain unevenly distributed…
AfriSUD: A Dependency Treebank Collection for Evaluating Models on African Languages
Happy Buzaaba, Cheikh Mouhamadou Bamba Dione, David Ifeoluwa Adelani +15
Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP. We aim to bridge this gap by introdu…
YoNER: A New Yorùbá Multi-domain Named Entity Recognition Dataset
Peace Busola Falola, Jesujoba O. Alabi, Solomon O. Akinola +3
Named Entity Recognition (NER) is a foundational NLP task, yet research in Yorùbá has been constrained by limited and domain-specific resources. Existing resources, such as Masakha…
Multilinguality as Sense Adaptation
Jan Christian Blaise Cruz, David Ifeoluwa Adelani, Alham Fikri Aji
We approach multilinguality as sense adaptation: aligning latent meaning representations across languages rather than relying solely on shared parameters and scale. In this paper,…
Afri-MCQA: Multimodal Cultural Question Answering for African Languages
Atnafu Lambebo Tonja, Srija Anand, Emilio Villa-Cueva +16
Africa is home to over one-third of the world's languages, yet remains underrepresented in AI research. We introduce Afri-MCQA, the first Multilingual Cultural Question-Answering b…
AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages
Hao Yu, Tianyi Xu, Michael A. Hedderich +3
Large language models (LLMs) are increasingly multilingual, yet open models continue to underperform relative to proprietary systems, with the gap most pronounced for African langu…
Ibom NLP: A Step Toward Inclusive Natural Language Processing for Nigeria's Minority Languages
Oluwadara Kalejaiye, Luel Hagos Beyene, David Ifeoluwa Adelani +4
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 linguistic…
AfriMTEB and AfriE5: Benchmarking and Adapting Text Embedding Models for African Languages
Kosei Uemura, Miaoran Zhang, David Ifeoluwa Adelani
Text embeddings are an essential building component of several NLP tasks such as retrieval-augmented generation which is crucial for preventing hallucinations in LLMs. Despite the…
DIVERS-Bench: Evaluating Language Identification Across Domain Shifts and Code-Switching
Jessica Ojo, Zina Kamel, David Ifeoluwa Adelani
Language Identification (LID) is a core task in multilingual NLP, yet current systems often overfit to clean, monolingual data. This work introduces DIVERS-BENCH, a comprehensive e…
Natural language processing for African languages
David Ifeoluwa Adelani
Recent advances in word embeddings and language models use large-scale, unlabelled data and self-supervised learning to boost NLP performance. Multilingual models, often trained on…
mSTEB: Massively Multilingual Evaluation of LLMs on Speech and Text Tasks
Luel Hagos Beyene, Vivek Verma, Min Ma +4
Large Language models (LLMs) have demonstrated impressive performance on a wide range of tasks, including in multimodal settings such as speech. However, their evaluation is often…
SSA-COMET: Do LLMs Outperform Learned Metrics in Evaluating MT for Under-Resourced African Languages?
Senyu Li, Jiayi Wang, Felermino D. M. A. Ali +7
Evaluating machine translation (MT) quality for under-resourced African languages remains a significant challenge, as existing metrics often suffer from limited language coverage a…
Improving Multilingual Math Reasoning for African Languages
Odunayo Ogundepo, Akintunde Oladipo, Kelechi Ogueji +3
Researchers working on low-resource languages face persistent challenges due to limited data availability and restricted access to computational resources. Although most large lang…
Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead
Jesujoba O. Alabi, Michael A. Hedderich, David Ifeoluwa Adelani +1
With over 2,000 languages and potentially millions of speakers, Africa represents one of the richest linguistic regions in the world. Yet, this diversity is scarcely reflected in s…
The NaijaVoices Dataset: Cultivating Large-Scale, High-Quality, Culturally-Rich Speech Data for African Languages
Chris Emezue, NaijaVoices Community, Busayo Awobade +8
The development of high-performing, robust, and reliable speech technologies depends on large, high-quality datasets. However, African languages -- including our focus, Igbo, Hausa…
SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +18
We present our shared task on text-based emotion detection, covering more than 30 languages from seven distinct language families. These languages are predominantly low-resource an…
Lugha-Llama: Adapting Large Language Models for African Languages
Happy Buzaaba, Alexander Wettig, David Ifeoluwa Adelani +1
Large language models (LLMs) have achieved impressive results in a wide range of natural language applications. However, they often struggle to recognize low-resource languages, in…
Multilingual Language Model Pretraining using Machine-translated Data
Jiayi Wang, Yao Lu, Maurice Weber +5
High-resource languages such as English, enables the pretraining of high-quality large language models (LLMs). The same can not be said for most other languages as LLMs still under…
Warmup Generations: A Task-Agnostic Approach for Guiding Sequence-to-Sequence Learning with Unsupervised Initial State Generation
Senyu Li, Zipeng Sun, Jiayi Wang +4
Traditional supervised fine-tuning (SFT) strategies for sequence-to-sequence tasks often train models to directly generate the target output. Recent work has shown that guiding mod…
INJONGO: A Multicultural Intent Detection and Slot-filling Dataset for 16 African Languages
Hao Yu, Jesujoba O. Alabi, Andiswa Bukula +19
Slot-filling and intent detection are well-established tasks in Conversational AI. However, current large-scale benchmarks for these tasks often exclude evaluations of low-resource…
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +45
People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition--an umbrella term for several NLP tasks--impacts various applications wit…
AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages
Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele +24
Hate speech and abusive language are global phenomena that need socio-cultural background knowledge to be understood, identified, and moderated. However, in many regions of the Glo…