EMBEDDIA project: Cross-Lingual Embeddings for Less- Represented Languages in European News Media

Senja Pollak, Andraž Pelicon


Abstract
EMBEDDIA project developed a range of resources and methods for less-resourced EU languages, focusing on applications for media industry, including keyword extraction, comment moderation and article generation.
Anthology ID:
2022.eamt-1.36
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:
293–294
Language:
URL:
https://aclanthology.org/2022.eamt-1.36
DOI:
Bibkey:
Cite (ACL):
Senja Pollak and Andraž Pelicon. 2022. EMBEDDIA project: Cross-Lingual Embeddings for Less- Represented Languages in European News Media. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 293–294, Ghent, Belgium. European Association for Machine Translation.
Cite (Informal):
EMBEDDIA project: Cross-Lingual Embeddings for Less- Represented Languages in European News Media (Pollak & Pelicon, EAMT 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.eamt-1.36.pdf