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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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