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---
language:
- pt
- de
- fr
- sv
- it
- es
- nl
license: mit
pretty_name: JWLang Corpus
datasets:
- jwlang
tags:
- automatic-speech-recognition
- speech
- dataset
- jw.org
- multilingual
- whisper
viewer: true
dataset_info:
- config_name: de
  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: 44420148.0
    num_examples: 949
  - name: test
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    num_examples: 119
  - name: val
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    num_examples: 119
  download_size: 223549840
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- config_name: es
  features:
  - name: client_id
    dtype: string
  - name: audio
    dtype: audio
  - name: sentence
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  - name: language
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  - name: split
    dtype: string
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- config_name: fr
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  - name: sentence
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  - name: language
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  - name: split
    dtype: string
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  download_size: 102271952
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- config_name: it
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    dtype: string
  - name: audio
    dtype: audio
  - name: sentence
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  - name: language
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  download_size: 49525612
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- config_name: nl
  features:
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    dtype: string
  - name: audio
    dtype: audio
  - name: sentence
    dtype: string
  - name: language
    dtype: string
  - name: split
    dtype: string
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  download_size: 53882775
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- config_name: pt
  features:
  - name: client_id
    dtype: string
  - name: audio
    dtype: audio
  - name: sentence
    dtype: string
  - name: language
    dtype: string
  - name: split
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  download_size: 340665914
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- config_name: sv
  features:
  - name: client_id
    dtype: string
  - name: audio
    dtype: audio
  - name: sentence
    dtype: string
  - name: language
    dtype: string
  - name: split
    dtype: string
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    num_examples: 89
  - name: val
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  download_size: 54362862
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configs:
- config_name: de
  data_files:
  - split: train
    path: de/train-*
  - split: test
    path: de/test-*
  - split: val
    path: de/val-*
- config_name: es
  data_files:
  - split: train
    path: es/train-*
  - split: test
    path: es/test-*
  - split: val
    path: es/val-*
- config_name: fr
  data_files:
  - split: train
    path: fr/train-*
  - split: test
    path: fr/test-*
  - split: val
    path: fr/val-*
- config_name: it
  data_files:
  - split: train
    path: it/train-*
  - split: test
    path: it/test-*
  - split: val
    path: it/val-*
- config_name: nl
  data_files:
  - split: train
    path: nl/train-*
  - split: test
    path: nl/test-*
  - split: val
    path: nl/val-*
- config_name: pt
  data_files:
  - split: train
    path: pt/train-*
  - split: test
    path: pt/test-*
  - split: val
    path: pt/val-*
- config_name: sv
  data_files:
  - split: train
    path: sv/train-*
  - split: test
    path: sv/test-*
  - split: val
    path: sv/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](https://www.jw.org) website. It is designed for training and fine-tuning automatic speech recognition (ASR) models, specifically OpenAI Whisper. The dataset is stored in Parquet format on Hugging Face, with original audio files in MP3 format and corresponding text files. The data were downloaded in June 2024.

## Splits
- Train
- Validation
- Test

## Usage
To load and use the dataset:

```python
from datasets import load_dataset

dataset = load_dataset("M2LabOrg/jwlang")
```

## Example Data
Example text snippet from the dataset:
```json
{
  "audio": "path/to/audio.mp3",
  "text": "Example subtitle text."
}
```

## License
```
This dataset is private and intended for internal use only.
```

## Citation
If you use this dataset, please cite:

```
@article{jwlang_corpus,
  title={JWLang Corpus from jw.org Videos for ASR Training},
  author={Michel Mesquita},
  journal={Unpublished},
  year={2024},
  note={Data downloaded from jw.org in June 2024 and processed by M. Mesquita}
}
```

## Contact
For any questions or issues, please contact [Michel Mesquita](mailto:mmeclimate@gmail.com).