Papers by Tolulope Ogunremi
ÌròyìnSpeech: A Multi-purpose Yorùbá Speech Corpus (2024.lrec-main)
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| Challenge: | rynSpeech corpus is a dataset that can be used for both Text-to-Speecher (TTS) and Automatic Speech Recognition (ASR) speakers of many African languages have no access to voice-enabled applications in their native languages. |
| Approach: | They propose a dataset to collect Yorùbá speech data that can be used for both TTS and ASR tasks. |
| Outcome: | The proposed dataset can generate a good quality model with as little as 5 hours of speech . the results are consistent with previous studies on the Yorùbá language . |
Mini But Mighty: Efficient Multilingual Pretraining with Linguistically-Informed Data Selection (2023.findings-eacl)
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| Challenge: | AfriBERTa shows that training transformer models from scratch on 1GB of data from many unrelated African languages outperforms massively multilingual models on downstream NLP tasks. |
| Approach: | They propose that training on smaller amounts of data but from related languages could match the performance of models trained on large, unrelated data. |
| Outcome: | The proposed model outperforms models trained on large, unrelated datasets on downstream NLP tasks. |