Bootstrapping a Hybrid MT System to a New Language Pair

João António Rodrigues, Nuno Rendeiro, Andreia Querido, Sanja Štajner, António Branco


Abstract
The usual concern when opting for a rule-based or a hybrid machine translation (MT) system is how much effort is required to adapt the system to a different language pair or a new domain. In this paper, we describe a way of adapting an existing hybrid MT system to a new language pair, and show that such a system can outperform a standard phrase-based statistical machine translation system with an average of 10 persons/month of work. This is specifically important in the case of domain-specific MT for which there is not enough parallel data for training a statistical machine translation system.
Anthology ID:
L16-1438
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2762–2765
Language:
URL:
https://www.aclweb.org/anthology/L16-1438
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/L16-1438.pdf