---
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  journal={Unpublished},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).