|
--- |
|
dataset_info: |
|
features: |
|
- name: audio |
|
dtype: |
|
audio: |
|
sampling_rate: 16000 |
|
- name: text |
|
dtype: string |
|
- name: gender |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 4274917077.83 |
|
num_examples: 36009 |
|
- name: test |
|
num_bytes: 475541653.87 |
|
num_examples: 4001 |
|
download_size: 4571561616 |
|
dataset_size: 4750458731.7 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
- split: test |
|
path: data/test-* |
|
license: cc-by-4.0 |
|
task_categories: |
|
- text-to-speech |
|
language: |
|
- wo |
|
pretty_name: woloftts |
|
size_categories: |
|
- 10K<n<100K |
|
--- |
|
# Wolof TTS |
|
## Dataset Description |
|
This is a [Wolof](https://en.wikipedia.org/wiki/Wolof_language) Text To Speech (TTS) dataset collected by [Baamtu Datamation](https://baamtu.com/) as part of the [AI4D African language program](https://k4all.org/project/language-dataset-fellowship/). |
|
The original dataset is hosted on [Zenodo](https://zenodo.org/records/4498861#.YXU2A3X7R-M) and it contains recordings from two (02) natif Wolof speakers (a `male` and `female` voice). Each speaker recored __more than 20,000 sentences__. |
|
|
|
### Speaking time: |
|
|
|
-- Male: 22h 28mn 41s |
|
-- Female: 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} |
|
} |
|
``` |
|
This dataset was made available on HuggingFace through [GalsenAI](https://galsen.ai/)'s mission to strengthen Senegal's AI ecosystem. It was cleaned and structured by [Derguene Mbaye](https://huggingface.co/derguene), then uploaded and documented by [Alwaly Ndiaye](https://huggingface.co/Alwaly). |