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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: 69142263.41007572
num_examples: 2303
- name: validation
num_bytes: 17165592.74192428
num_examples: 576
download_size: 85971677
dataset_size: 86307856.15200001
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
# Dataset Details
This is the Indonesia-to-English dataset for Speech Translation task. This dataset is acquired from [CoVoST](https://huggingface.co/datasets/facebook/covost2).
CoVoST2 is end-to-end speech-to-text translation. The dataset is based on using Mozillas open-source Common Voice database of
crowdsourced voice recordings. CoVoST2 is covering several languages, one of which is Indonesia. The Indonesian data has 2879 utterances and approximately 2 hours and 58 minutes of audio data.
# Processing Steps
Before the Fleurs dataset is extracted, there are some preprocessing steps to the data:
1. Remove some unused columns.
2. Switch the `id` column position into the first column.
3. Rename the `sentence` column to `text_indo` and `translation` column to `text_en`.
4. Cast the audio column into Audio object.
5. Split into Train and Validation.
# Dataset Structure
```
DatasetDict({
train: Dataset({
features: ['id', 'audio', 'text_indo', 'text_en'],
num_rows: 2892
}),
validation: Dataset({
features: ['id', 'audio', 'text_indo', 'text_en'],
num_rows: 724
}),
})
```
# Citation
```
@article
@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. |