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.- Anthology ID:
- 2023.findings-acl.665
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2023
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10466–10475
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2023.findings-acl.665/
- DOI:
- 10.18653/v1/2023.findings-acl.665
- Cite (ACL):
- Abhinav Joshi, Susmit Agrawal, and Ashutosh Modi. 2023. ISLTranslate: Dataset for Translating Indian Sign Language. In Findings of the Association for Computational Linguistics: ACL 2023, pages 10466–10475, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- ISLTranslate: Dataset for Translating Indian Sign Language (Joshi et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2023.findings-acl.665.pdf