Abstract
Portuguese Sign Language (LGP) is the official language in deaf education in Portugal. Current approaches in developing a translation system between European Portuguese and LGP rely on hand-crafted rules. In this paper, we present a fully automatic corpora-driven rule-based machine translation system between European Portuguese and LGP glosses, and also two neural machine translation models. We also contribute with the LGP-5-Domain corpus, composed of five different text domains, built with the help of our rule-based system, and used to train the neural models. In addition, we provide a gold collection, annotated by LGP experts, that can be used for future evaluations. Compared with the only similar available translation system, PE2LGP, results are always improved with the new rule-based model, which competes for the highest scores with one of the neural models.- Anthology ID:
- 2023.findings-emnlp.766
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 11452–11460
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.766
- DOI:
- 10.18653/v1/2023.findings-emnlp.766
- Cite (ACL):
- Catarina Sousa, Luisa Coheur, and Mara Moita. 2023. Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 11452–11460, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language (Sousa et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2023.findings-emnlp.766.pdf