metadata

annotations_creators:
  - expert-generated
  - crowdsourced
language_creators:
  - crowdsourced
  - expert-generated
language:
  - rw
license:
  - cc-by-4.0
size_categories:
  - 1K<n<10K
task_categories:
  - automatic-speech-recognition
tags:
  - speech-recognition
  - fleurs-dataset
pretty_name: Fleurs dataset Kinyarwanda

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