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--- |
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annotations_creators: |
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- expert-generated |
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- crowdsourced |
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language_creators: |
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- crowdsourced |
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- expert-generated |
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language: |
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- rw |
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license: |
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- cc-by-4.0 |
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size_categories: |
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- 1K<n<10K |
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task_categories: |
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- automatic-speech-recognition |
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tags: |
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- speech-recognition |
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- fleurs-dataset |
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pretty_name: Fleurs dataset Kinyarwanda |
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--- |
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# Fleur Kinyarwanda dataset |
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Fleur is a multilingual text and audio dataset. The original dataset was created by [Google](https://huggingface.co/datasets/google/fleurs) . The dataset can be used when building speech to text, speech to text translation and speech to speech translation. It is a good tool to benchmark speech application especially across languages. As of present Kinyarwanda did not have a fleur dataset hindering opportunities for building Kinyarwanda speech technology. |
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This dataset was created by 29 linguists that participated in the Training NLP for Linguist with a focus on Machine translation. |
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## Dataset Creation |
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The recordings are made of 2-4 different recordings for each sentence |
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### Data Fields |
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The data fields are the same among all splits. |
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- **id** (int): ID of audio sample |
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- **num_samples** (int): Number of float values |
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- **path** (str): Path to the audio file |
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- **audio** (dict): Audio object including loaded audio array, sampling rate and path ot audio |
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- **raw_transcription** (str): The non-normalized transcription of the audio file |
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- **transcription** (str): Transcription of the audio file |
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- **gender** (int): Class id of gender |
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- **lang_id** (int): Class id of language |
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- **lang_group_id** (int): Class id of language group |
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### Contribution |
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Thanks to all the linguist who contributed and their teacher Samuel Olanrewaju and thanks [Kleber Kabanda](https://huggingface.co/Kleber) for curating and uploading the dataset |
