Datasets:
Fleur Kinyarwanda dataset
Fleur is a multilingual text and audio dataset. The original dataset was created by Google . 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.
This dataset was created by 29 linguists that participated in the Training NLP for Linguist with a focus on Machine translation.
Dataset Creation
The recordings are made of 2-4 different recordings for each sentence
Data Fields
The data fields are the same among all splits.
- id (int): ID of audio sample
- num_samples (int): Number of float values
- path (str): Path to the audio file
- audio (dict): Audio object including loaded audio array, sampling rate and path ot audio
- raw_transcription (str): The non-normalized transcription of the audio file
- transcription (str): Transcription of the audio file
- gender (int): Class id of gender
- lang_id (int): Class id of language
- lang_group_id (int): Class id of language group
Contribution
Thanks to all the linguist who contributed and their teacher Samuel Olanrewaju and thanks Kleber Kabanda for curating and uploading the dataset
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