Constrained translation has improved statistical machine translation (SMT) by
combining it with translation memory
(TM) at sentence-level. In this paper, we
propose using a constrained word lattice,
which encodes input phrases and TM constraints together, to combine SMT and TM
at phrase-level. Experiments on English–
Chinese and English–French show that
our approach is significantly better than
previous combination methods, including
sentence-level constrained translation and
a recent phrase-level combination.
Erk, Katrin and Smith, Noah A., (eds.)
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics.
2.
Association for Computational Linguistics (ACL).
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
People Programme (Marie Curie Actions) of the European Union’s Framework Programme (FP7/2007- 2013) under REA grant agreement no 317471., ADAPT Centre for Digital Content Technology is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.
ID Code:
23359
Deposited On:
24 May 2019 15:12 by
Thomas Murtagh
. Last Modified 24 May 2019 15:12