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---
language:
- pt
license: mit
datasets:
- jwlang
tags:
- automatic-speech-recognition
- speech
- dataset
viewer: true
dataset_info:
config_name: pt
features:
- name: client_id
dtype: string
- name: audio
dtype: audio
- name: sentence
dtype: string
- name: language
dtype: string
- name: split
dtype: string
splits:
- name: train
num_bytes: 45540940.152
num_examples: 1004
- name: test
num_bytes: 5906213.0
num_examples: 126
- name: val
num_bytes: 5474968.0
num_examples: 125
download_size: 113555414
dataset_size: 56922121.152
configs:
- config_name: pt
data_files:
- split: train
path: pt/train-*
- split: test
path: pt/test-*
- split: val
path: pt/val-*
---
# JWLang Corpus
## Dataset Summary
The JWLang Corpus is a collection of audio and corresponding text data from JW Broadcasting videos available on the jw.org website. It is intended for training and fine-tuning automatic speech recognition (ASR) models, specifically OpenAI Whisper.
## Dataset Structure
- Number of samples: 10,000
- Data format: Audio (WAV) and Text (SRT)
- Size: 5 GB
## Splits
| Split | Number of samples |
|------------|-------------------|
| Train | 8,000 |
| Validation | 1,000 |
| Test | 1,000 |
## Usage
To load and use the dataset:
```python
from datasets import load_dataset
dataset = load_dataset("M2LabOrg/JWLang_Corpus")
```
## Example Data
Example text snippet from the dataset:
```
{
"audio": "path/to/audio.wav",
"text": "Example subtitle text."
}
```
## License
```
CC BY-SA 4.0
```
## Citation
If you use this dataset, please cite:
```
@article{jwlang_corpus,
title={JWLang Corpus for ASR Training},
author={Michel Mesquita},
journal={Unpublished},
year={2024},
}
```
## Contact
For any questions or issues, please contact [Michel Mesquita](mailto:mmeclimate@gmail.com). |