ISLTranslate: Dataset for Translating Indian Sign Language
Abhinav Joshi, Susmit Agrawal, Ashutosh Modi
Abstract
Sign languages are the primary means of communication for many hard-of-hearing people worldwide. Recently, to bridge the communication gap between the hard-of-hearing community and the rest of the population, several sign language translation datasets have been proposed to enable the development of statistical sign language translation systems. However, there is a dearth of sign language resources for the Indian sign language. This resource paper introduces ISLTranslate, a translation dataset for continuous Indian Sign Language (ISL) consisting of 31k ISL-English sentence/phrase pairs. To the best of our knowledge, it is the largest translation dataset for continuous Indian Sign Language. We provide a detailed analysis of the dataset. To validate the performance of existing end-to-end Sign language to spoken language translation systems, we benchmark the created dataset with a transformer-based model for ISL translation.
BibTeX
@inproceedings{joshi-etal-2023-isltranslate,
title = "{ISLT}ranslate: Dataset for Translating {I}ndian {S}ign {L}anguage",
author = "Joshi, Abhinav and
Agrawal, Susmit and
Modi, Ashutosh",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.665/",
doi = "10.18653/v1/2023.findings-acl.665",
pages = "10466--10475"
}