Abraham Owodunni

I am a Ph.D. student in Computer Science and Engineering at The Ohio State University where I have been privilaged be advised by the awesome Prof. Sachin Kumar. Before that, I was a researcher at IntronHealth during which I work on buidling language and speech models to African languages and accents (including MENA).

Right now, my research is focused on multilingual knowledge representation, knowledge transfer, resource-efficient NLP and building robust models that works for diverse lanuages and dialects.

Beyond the technical aspect of research, I worked on creating national AI policies within Nigerian and Africa, I enjoy mentoring new folks that are interested in getting into AI research and I love building and nurturing open science ML communities. You’ll find me around Masakane, ML Collective, Cohere Labs and a few other communities. I firmly believe in democratizing access to knowledge, fostering collaborative ecosystems, and championing the ethos of shared discovery.

If I’m not doing AI research, you can find me playing Pool, Lawn and Table Tennis (I suck at both though), reading books and listening to podcasts. Podcast recommendations: How To Take Over The World

news

May 19, 2025	Our papers `The NaijaVoices Dataset: Cultivating Large-Scale, High-Quality, Culturally-Rich Speech Data for African Languages` got accetped to Interspeech 2025!
May 15, 2025	Our papers `AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset` got accetped to ACL Main 2025! Joint work by partners from Google, PATH, Intron and Sinsoke.
Sep 2, 2024	I served as the Publication chair for the MRL 2024 Workshop at EMNLP. Checkout our proceedings.
Aug 16, 2024	I resumed my Ph.D. in Computer Science and Engineering at OSU.
Jun 4, 2024	2 papers on TTS and STT got accetped to Interspeech 2024! Find them here [1, 2].

latest posts

selected publications

Bloom Library: Multimodal Datasets in 300+ Languages for a Variety of Downstream Tasks

Colin Leong, Joshua Nemecek, Jacob Mansdorfer, and 3 more authors

In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Dec 2022

Abs

We present Bloom Library, a linguistically diverse set of multimodal and multilingual datasets for language modeling, image captioning, visual storytelling, and speech synthesis/recognition. These datasets represent either the most, or among the most, multilingual datasets for each of the included downstream tasks. In total, the initial release of the Bloom Library datasets covers 363 languages across 32 language families. We train downstream task models for various languages represented in the data, showing the viability of the data for future work in low-resource, multimodal NLP and establishing the first known baselines for these downstream tasks in certain languages (e.g., Bisu [bzi], with an estimated population of 700 users). Some of these first-of-their-kind baselines are comparable to state-of-the-art performance for higher-resourced languages. The Bloom Library datasets are released under Creative Commons licenses on the Hugging Face datasets hub to catalyze more linguistically diverse research in the included downstream tasks.
ICLR: AfricaNLP

Koya: A Recommender System for Large Language Model Selection

Abraham Toluwase Owodunni, and Chris Chinenye Emezue

In 4th Workshop on African Natural Language Processing, Dec 2023