|
--- |
|
dataset_info: |
|
features: |
|
- name: audio |
|
dtype: audio |
|
- name: text_ga |
|
dtype: string |
|
- name: text_en |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 4209155993.0 |
|
num_examples: 15090 |
|
download_size: 3452146050 |
|
dataset_size: 4209155993.0 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
--- |
|
|
|
# Dataset Details |
|
|
|
Synthetic audio dataset, created using Azure text-to-speech service. |
|
The bilingual text is a portion of the Wikimedia dataset, consisting of 7545 text segments. |
|
The dataset comprises two sets of audio data, one with a female voice (OrlaNeural) and the other with a male voice (ColmNeural). |
|
It includes more than 34 hours of audio data (34:23:12) for 15,090 utterances. |
|
|
|
|
|
## Dataset Structure |
|
|
|
``` |
|
Dataset({ |
|
features: ['audio', 'text_ga', 'text_en'], |
|
num_rows: 15090 |
|
}) |
|
``` |
|
|
|
## Citation |
|
|
|
``` |
|
@inproceedings{moslem2024leveraging, |
|
title={Leveraging Synthetic Audio Data for End-to-End Low-Resource Speech Translation}, |
|
author={Moslem, Yasmin}, |
|
booktitle={Proceedings of the 2024 International Conference on Spoken Language Translation (IWSLT 2024)}, |
|
year={2024}, |
|
month={April} |
|
} |
|
``` |
|
|
