Search Results for author: Tejumade Afonja

Found 7 papers, 1 papers with code

Towards Biologically Plausible and Private Gene Expression Data Generation

1 code implementation7 Feb 2024 Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz

In this paper, we initiate a systematic analysis of how DP generative models perform in their natural application scenarios, specifically focusing on real-world gene expression data.

Benchmarking

MargCTGAN: A "Marginally'' Better CTGAN for the Low Sample Regime

no code implementations16 Jul 2023 Tejumade Afonja, Dingfan Chen, Mario Fritz

The potential of realistic and useful synthetic data is significant.

AfriNames: Most ASR models "butcher" African Names

no code implementations1 Jun 2023 Tobi Olatunji, Tejumade Afonja, Bonaventure F. P. Dossou, Atnafu Lambebo Tonja, Chris Chinenye Emezue, Amina Mardiyyah Rufai, Sahib Singh

Useful conversational agents must accurately capture named entities to minimize error for downstream tasks, for example, asking a voice assistant to play a track from a certain artist, initiating navigation to a specific location, or documenting a laboratory result for a patient.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Proceedings of the NeurIPS 2021 Workshop on Machine Learning for the Developing World: Global Challenges

no code implementations10 Jan 2023 Paula Rodriguez Diaz, Tejumade Afonja, Konstantin Klemmer, Aya Salama, Niveditha Kalavakonda, Oluwafemi Azeez, Simone Fobi

These are the proceedings of the 5th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) on December 14th, 2021.

Learning Nigerian accent embeddings from speech: preliminary results based on SautiDB-Naija corpus

no code implementations12 Dec 2021 Tejumade Afonja, Oladimeji Mudele, Iroro Orife, Kenechi Dukor, Lawrence Francis, Duru Goodness, Oluwafemi Azeez, Ademola Malomo, Clinton Mbataku

We describe how the corpus was created and curated as well as preliminary experiments with accent classification and learning Nigerian accent embeddings.

Classification

Proceedings of the NeurIPS 2020 Workshop on Machine Learning for the Developing World: Improving Resilience

no code implementations12 Jan 2021 Tejumade Afonja, Konstantin Klemmer, Aya Salama, Paula Rodriguez Diaz, Niveditha Kalavakonda, Oluwafemi Azeez

These are the proceedings of the 4th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) on Saturday, December 12th 2020.

BIG-bench Machine Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.