QRev: Machine Translation of User Reviews: What Influences the Translation Quality?

Maja Popovic


Abstract
This project aims to identify the important aspects of translation quality of user reviews which will represent a starting point for developing better automatic MT metrics and challenge test sets, and will be also helpful for developing MT systems for this genre. We work on two types of reviews: Amazon products and IMDb movies, written in English and translated into two closely related target languages, Croatian and Serbian.
Anthology ID:
2020.eamt-1.52
Volume:
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
Month:
November
Year:
2020
Address:
Lisboa, Portugal
Editors:
André Martins, Helena Moniz, Sara Fumega, Bruno Martins, Fernando Batista, Luisa Coheur, Carla Parra, Isabel Trancoso, Marco Turchi, Arianna Bisazza, Joss Moorkens, Ana Guerberof, Mary Nurminen, Lena Marg, Mikel L. Forcada
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
461–462
Language:
URL:
https://aclanthology.org/2020.eamt-1.52
DOI:
Bibkey:
Cite (ACL):
Maja Popovic. 2020. QRev: Machine Translation of User Reviews: What Influences the Translation Quality?. In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, pages 461–462, Lisboa, Portugal. European Association for Machine Translation.
Cite (Informal):
QRev: Machine Translation of User Reviews: What Influences the Translation Quality? (Popovic, EAMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.eamt-1.52.pdf