metadata
dataset_info:
features:
- name: audio
dtype: audio
- name: translation
dtype: string
splits:
- name: train
num_bytes: 885158053.092
num_examples: 7478
- name: dev
num_bytes: 330788279.48
num_examples: 1120
- name: test
num_bytes: 44484347
num_examples: 347
download_size: 1105429263
dataset_size: 1260430679.572
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: dev
path: data/dev-*
- split: test
path: data/test-*
license: cc-by-nc-sa-4.0
task_categories:
- automatic-speech-recognition
- text-to-speech
- translation
language:
- ga
- en
size_categories:
- 1K<n<10K
Dataset details
IWSLT 2023/2024 dataset for Irish-to-English speech translation, as originally found on this GitHub repository. The audio data consists of the Common Voice and Living Audio (IDLAK) datasets.
Data available since: Irish-English Speech Translation Shared Task@IWSLT-2023 and 2024
License: CC BY-NC-SA 4.0
Includes text/audio: yes
Shared Task Organisers 2023: Ojha, Atul Kr.; Judge, John; McCrae, John P.
Shared Task Organisers 2024: Ojha, Atul Kr.; McCrae, John P.
Contact: [email protected], [email protected]
Contributor/©holder: Insight Centre for Data Analytics, Data Science Institute, University of Galway, Ireland and ADAPT Centre, Ireland
How to load the dataset
from datasets import load_dataset, DatasetDict
iwslt2023_gaen = DatasetDict()
iwslt2023_gaen["train"] = load_dataset("ymoslem/IWSLT2023-GA-EN",
split="train",
trust_remote_code=True,
)
iwslt2023_gaen["dev"] = load_dataset("ymoslem/IWSLT2023-GA-EN",
split="dev",
trust_remote_code=True,
)
iwslt2023_gaen["test"] = load_dataset("ymoslem/IWSLT2023-GA-EN",
split="test",
trust_remote_code=True,
)
Dataset statistics
DatasetDict({
train: Dataset({
features: ['audio', 'translation'],
num_rows: 7478
})
dev: Dataset({
features: ['audio', 'translation'],
num_rows: 1120
})
test: Dataset({
features: ['audio', 'translation'],
num_rows: 347
})
})
Citation
@inproceedings{agrawal-etal-2023-findings,
title = "{FINDINGS} {OF} {THE} {IWSLT} 2023 {EVALUATION} {CAMPAIGN}",
author = {Agarwal, Milind and
Agrawal, Sweta and
Anastasopoulos, Antonios and
Bentivogli, Luisa and
Bojar, Ond{\v{r}}ej and
Borg, Claudia and
Carpuat, Marine and
Cattoni, Roldano and
Cettolo, Mauro and
Chen, Mingda and
Chen, William and
Choukri, Khalid and
Chronopoulou, Alexandra and
Currey, Anna and
Declerck, Thierry and
Dong, Qianqian and
Duh, Kevin and
Est{\`e}ve, Yannick and
Federico, Marcello and
Gahbiche, Souhir and
Haddow, Barry and
Hsu, Benjamin and
Mon Htut, Phu and
Inaguma, Hirofumi and
Javorsk{\'y}, D{\'a}vid and
Judge, John and
Kano, Yasumasa and
Ko, Tom and
Kumar, Rishu and
Li, Pengwei and
Ma, Xutai and
Mathur, Prashant and
Matusov, Evgeny and
McNamee, Paul and
P. McCrae, John and
Murray, Kenton and
Nadejde, Maria and
Nakamura, Satoshi and
Negri, Matteo and
Nguyen, Ha and
Niehues, Jan and
Niu, Xing and
Kr. Ojha, Atul and
E. Ortega, John and
Pal, Proyag and
Pino, Juan and
van der Plas, Lonneke and
Pol{\'a}k, Peter and
Rippeth, Elijah and
Salesky, Elizabeth and
Shi, Jiatong and
Sperber, Matthias and
St{\"u}ker, Sebastian and
Sudoh, Katsuhito and
Tang, Yun and
Thompson, Brian and
Tran, Kevin and
Turchi, Marco and
Waibel, Alex and
Wang, Mingxuan and
Watanabe, Shinji and
Zevallos, Rodolfo},
editor = "Salesky, Elizabeth and
Federico, Marcello and
Carpuat, Marine",
booktitle = "Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada (in-person and online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.iwslt-1.1",
doi = "10.18653/v1/2023.iwslt-1.1",
pages = "1--61",
abstract = "This paper reports on the shared tasks organized by the 20th IWSLT Conference. The shared tasks address 9 scientific challenges in spoken language translation: simultaneous and offline translation, automatic subtitling and dubbing, speech-to-speech translation, multilingual, dialect and low-resource speech translation, and formality control. The shared tasks attracted a total of 38 submissions by 31 teams. The growing interest towards spoken language translation is also witnessed by the constantly increasing number of shared task organizers and contributors to the overview paper, almost evenly distributed across industry and academia.",
}