Datasets:
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README.md
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path: data/dev-*
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- split: test
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path: data/test-*
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---
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path: data/dev-*
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- split: test
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path: data/test-*
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task_categories:
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- automatic-speech-recognition
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- translation
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language:
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- bm
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size_categories:
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- 1K<n<10K
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---
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# Koumankan4Dyula: Parallel Dyula - French Dataset for Machine Learning
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## Overview
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The Koumankan4Dyula corpus consists of approximately 15 hours i.e. 10,929 recordings of Dioula language audio along with the corresponding texts and their translations into French and English. Dioula is a low-resource language spoken by over 16.4 million people in several West African countries. This corpus is part of the Koumankan project, which offers a scalable and cost-effective method to expand the CommonVoice dataset to include the Dyula language and other African languages. It will serve as a benchmark for training models for automatic speech translation in Dioula as well as for automatic speech recognition or machine translation models from Dioula to French and English.
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## Data Splits
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| split |percentage|Nm. records| Num hour |
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|:-----:|:--------:|----------:|---------:|
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| Train | 73% | 8065 | 8h 9m |
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| Valid | 14% | 1471 | 1h 36m |
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| Test | 13% | 1393 | 44m 36s |
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### Maintenance
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* This dataset is supposed to be actively maintained.
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### Benchmarks:
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- `Coming soon`
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## License
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- `CC-BY-SA-4.0`
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## Version
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- `1.0.0`
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## Acknowledgements
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This dataset collection efforts have been supported by International Development Research Centre (IDRC) and Swedish International Development Cooperation Agency (SIDA),
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managed by African Center for Technology Studies (ACTS) in collaboration with the Université Virtuelle de Côte d'Ivoire (UVCI) through the programme Artificial Intelligence for Development (AI4D) Africa.
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## Contacts
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- `[email protected]`
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- `[email protected]`
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