Obtaining high-quality machine translations is still a long way off. A postediting phase is required to improve the output of a machine translation system. An alternative is the so called computerassisted translation. In this framework, a human translator interacts with the system in order to obtain high-quality translations. A statistical phrase-based approach to computer-assisted translation is described in this article. A new decoder algorithm for interactive search is also presented, that combines monotone and nonmonotone search. The system has been assessed in the TransType-2 project for the translation of several printer manuals, from (to) English to (from) Spanish, German and French.
In REF a phrase-based approach is presented.
Statistical Phrase-Based Models For Interactive Computer-Assisted Translation
International Conference On Computational Linguistics And Annual Meeting Of The Association For Computational Linguistics - Poster Sessions
Computer Science