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| ARTICLE =""" | |
| **Motivation** | |
| In Africa, like in other continents of the world, people access vital information mainly through their mobile phones. Therefore the need for voice-enabled applications can be found in all sectors, from health, food to more fun (games, social media). | |
| Existing speech recognition services are not available in many African languages, and the speakers of these languages are excluded from the benefits of voice-enabled technologies. | |
| This dataset will boost speech technologies (like speech-to-text, text-to-speech, speech translation, and modeling) for African languages, which hitherto had little or no public dataset. | |
| **Note:** This is a continuous effort. This sprint is just to kick-start the event. | |
| **Benefits of such a dataset** | |
| - Useful dataset to introduce people to audio-related Machine Learning. It can be used as a simple training and/or evaluation dataset for speech processing tasks. | |
| **About the dataset** | |
| The data (metadat,text, and audio recording) are uploaded to [a public Hugging Face dataset](https://huggingface.co/datasets/chrisjay/crowd-speech-africa). | |
| We do not collect your name, address or other sensitive information. | |
| If for some reason you want to remove your entry, please reach out by email. | |
| **Contact** | |
| In case of questions, issues or anything contact Chris Emezue at: | |
| - chris@huggingface.co | |
| """ |