GoURMET – Machine Translation for Low-Resourced Languages

Peggy van der Kreeft, Alexandra Birch, Sevi Sariisik, Felipe Sánchez-Martínez, Wilker Aziz


Abstract
The GoURMET project, funded by the European Commission’s H2020 program (under grant agreement 825299), develops models for machine translation, in particular for low-resourced languages. Data, models and software releases as well as the GoURMET Translate Tool are made available as open source.
Anthology ID:
2022.eamt-1.59
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:
339–340
Language:
URL:
https://aclanthology.org/2022.eamt-1.59
DOI:
Bibkey:
Cite (ACL):
Peggy van der Kreeft, Alexandra Birch, Sevi Sariisik, Felipe Sánchez-Martínez, and Wilker Aziz. 2022. GoURMET – Machine Translation for Low-Resourced Languages. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 339–340, Ghent, Belgium. European Association for Machine Translation.
Cite (Informal):
GoURMET – Machine Translation for Low-Resourced Languages (van der Kreeft et al., EAMT 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-3/2022.eamt-1.59.pdf