Using any machine translation source for fuzzy-match repair in a computer-aided translation setting

John E. Ortega, Felipe Sánchez-Martinez, Mikel L. Forcada


Abstract
When a computer-assisted translation (CAT) tool does not find an exact match for the source segment to translate in its translation memory (TM), translators must use fuzzy matches that come from translation units in the translation memory that do not completely match the source segment. We explore the use of a fuzzy-match repair technique called patching to repair translation proposals from a TM in a CAT environment using any available machine translation system, or any external bilingual source, regardless of its internals. Patching attempts to aid CAT tool users by repairing fuzzy matches and proposing improved translations. Our results show that patching improves the quality of translation proposals and reduces the amount of edit operations to perform, especially when a specific set of restrictions is applied.
Anthology ID:
2014.amta-researchers.4
Volume:
Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track
Month:
October 22-26
Year:
2014
Address:
Vancouver, Canada
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
42–53
Language:
URL:
https://aclanthology.org/2014.amta-researchers.4
DOI:
Bibkey:
Cite (ACL):
John E. Ortega, Felipe Sánchez-Martinez, and Mikel L. Forcada. 2014. Using any machine translation source for fuzzy-match repair in a computer-aided translation setting. In Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track, pages 42–53, Vancouver, Canada. Association for Machine Translation in the Americas.
Cite (Informal):
Using any machine translation source for fuzzy-match repair in a computer-aided translation setting (Ortega et al., AMTA 2014)
Copy Citation:
PDF:
https://aclanthology.org/2014.amta-researchers.4.pdf