Abstract
It is often a challenging task to build Machine Translation (MT) engines for a specific domain due to the lack of parallel data in that area. In this project, we develop a range of MT systems for 6 European languages (English, German, Italian, French, Polish and Irish) in all directions and in two domains (environment and economics).- Anthology ID:
- 2022.eamt-1.69
- Volume:
- Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
- Month:
- June
- Year:
- 2022
- Address:
- Ghent, Belgium
- Editors:
- Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 359–360
- Language:
- URL:
- https://aclanthology.org/2022.eamt-1.69
- DOI:
- Cite (ACL):
- Pintu Lohar, Guodong Xie, and Andy Way. 2022. Developing Machine Translation Engines for Multilingual Participatory Spaces. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 359–360, Ghent, Belgium. European Association for Machine Translation.
- Cite (Informal):
- Developing Machine Translation Engines for Multilingual Participatory Spaces (Lohar et al., EAMT 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2022.eamt-1.69.pdf