Statistical Phrase-Based Models for Interactive Computer-Assisted Translation
نویسندگان
چکیده
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.
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