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---
dataset_info:
features:
- name: id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text_indo
dtype: string
- name: text_en
dtype: string
splits:
- name: train
num_bytes: 35886292.768
num_examples: 1243
- name: validation
num_bytes: 24899653
num_examples: 792
- name: test
num_bytes: 26407823
num_examples: 844
download_size: 85945718
dataset_size: 87193768.768
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
language:
- id
- en
pretty_name: d
---
# Dataset Details
This is the Indonesia-to-English dataset for Speech Translation tasks. This dataset is acquired from [CoVoST2](https://huggingface.co/datasets/facebook/covost2).
CoVoST2 is a corpus that is intended for speech-to-text translation tasks. CoVoST2 consists of 21 languages that are translated into English, one of them is Indonesian.
This dataset approximately has 3 hours 6 minutes 58 seconds of audio data.
# Processing Steps
Before the data is extracted, there are some preprocessing steps to the data:
1. Checked the duplicate ids in each splits.
2. Checked the overlap ids in across of the splits.
3. Removed some of the columns, except ids, Indonesian audio, sentence, and translation.
4. Renamed column "sentence" into "text_indo" and column "translation" into "text_en".
# Dataset Structure
```
DatasetDict({
train: Dataset({
features: ['id', 'audio', 'text_indo', 'text_en'],
num_rows: 1243
}),
validation: Dataset({
features: ['id', 'audio', 'text_indo', 'text_en'],
num_rows: 792
}),
test: Dataset({
features: ['id', 'audio', 'text_indo', 'text_en'],
num_rows: 844
})
})
```
# Citation
```
@misc{wang2020covost,
title={CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus},
author={Changhan Wang and Anne Wu and Juan Pino},
year={2020},
eprint={2007.10310},
archivePrefix={arXiv},
primaryClass={cs.CL}
```
# Credits:
Huge thanks to [Yasmin Moslem](https://huggingface.co/ymoslem) for mentoring me.
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