M3TRA: integrating TM and MT for professional translators

Bram Bulté, Tom Vanallemeersch, Vincent Vandeghinste


Abstract
Translation memories (TM) and machine translation (MT) both are potentially useful resources for professional translators, but they are often still used independently in translation workflows. As translators tend to have a higher confidence in fuzzy matches than in MT, we investigate how to combine the benefits of TM retrieval with those of MT, by integrating the results of both. We develop a flexible TM-MT integration approach based on various techniques combining the use of TM and MT, such as fuzzy repair, span pretranslation and exploiting multiple matches. Results for ten language pairs using the DGT-TM dataset indicate almost consistently better BLEU, METEOR and TER scores compared to the MT, TM and NMT baselines.
Anthology ID:
2018.eamt-main.7
Volume:
Proceedings of the 21st Annual Conference of the European Association for Machine Translation
Month:
May
Year:
2018
Address:
Alicante, Spain
Editors:
Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Miquel Esplà-Gomis, Maja Popović, Celia Rico, André Martins, Joachim Van den Bogaert, Mikel L. Forcada
Venue:
EAMT
SIG:
Publisher:
Note:
Pages:
89–98
Language:
URL:
https://aclanthology.org/2018.eamt-main.7
DOI:
Bibkey:
Cite (ACL):
Bram Bulté, Tom Vanallemeersch, and Vincent Vandeghinste. 2018. M3TRA: integrating TM and MT for professional translators. In Proceedings of the 21st Annual Conference of the European Association for Machine Translation, pages 89–98, Alicante, Spain.
Cite (Informal):
M3TRA: integrating TM and MT for professional translators (Bulté et al., EAMT 2018)
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PDF:
https://aclanthology.org/2018.eamt-main.7.pdf