Datasets:
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 44100
- name: text
dtype: string
splits:
- name: train
num_bytes: 5938096417.625
num_examples: 19947
download_size: 4622425790
dataset_size: 5938096417.625
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- text-to-speech
language:
- wo
pretty_name: anta_women_tts
size_categories:
- 10K<n<100K
Anta Women TTS
Dataset Description
This is a cleaned version of the Wolof TTS dataset by GalsenAI.
We extracted the female
voice, denoised it and enhanced it with the Resemble Enhance library.
We also cleaned up the annotations by removing special characters, emojis, Arabic and Russian characters.
We've corrected a few annotation errors, but there are potentially many more to come.
Some lines and audios judged not qualitative enough have been removed from the dataset, reducing its size to 19918 annotated audios
.
Speaking time:
The speaking time is to be updated: 18h 47mn 19s
The text dataset comes from news websites, Wikipedia and self curated text.
Citation
You can access the project paper at https://arxiv.org/abs/2104.02516.
If you work on the dataset, please cite the authors below.
@dataset{thierno_ibrahima_diop_2021_4498861,
author = {Thierno Ibrahima Diop and
Demba AW and
Ami jaane and
Mamadou Badiane},
title = {WOLOF TTS(Text To Speech) Data},
month = feb,
year = 2021,
publisher = {Zenodo},
version = 1,
doi = {10.5281/zenodo.4498861},
url = {https://doi.org/10.5281/zenodo.4498861}
}
Acknowledgment
This work was carried out by Derguene and was made possible thanks to computing infrastructure support from Caytu Robotics. Many thanks to them and especially to Abdoulaye Faye for this support.