File size: 2,586 Bytes
65eeff2 5043acf 65eeff2 f0e3144 5043acf a2dc51a 482c387 66a51c1 ce2e254 bd67a81 c500d7d 5043acf a2dc51a 482c387 66a51c1 ce2e254 bd67a81 c500d7d 65eeff2 04b2f2f 65eeff2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 |
---
language:
- pt
license: mit
datasets:
- jwlang
tags:
- automatic-speech-recognition
- speech
- dataset
viewer: true
dataset_info:
- config_name: data/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: 45540263.152
num_examples: 1004
- name: test
num_bytes: 5906119.0
num_examples: 126
- name: val
num_bytes: 5474884.0
num_examples: 125
download_size: 56777789
dataset_size: 56921266.152
- config_name: data_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: 45540263.152
num_examples: 1004
- name: test
num_bytes: 5906119.0
num_examples: 126
- name: val
num_bytes: 5474884.0
num_examples: 125
download_size: 56777789
dataset_size: 56921266.152
configs:
- config_name: data/pt
data_files:
- split: train
path: data/pt/train-*
- split: test
path: data/pt/test-*
- split: val
path: data/pt/val-*
- config_name: data_pt
data_files:
- split: train
path: data_pt/train-*
- split: test
path: data_pt/test-*
- split: val
path: data_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:[email protected]). |