--- 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 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: atulkumar.ojha@insight-centre.org, shashwatup9k@gmail.com > 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.", } ```