Rule Selection with Soft Syntactic Features for String-to-Tree Statistical Machine Translation
Fabienne Braune, Nina Seemann, Alexander Fraser · 2015
In syntax-based machine translation, rule selection is the task of choosing the correct target side of a translation rule among rules with the same source side.We define a discriminative rule selection model for systems that have syntactic annotation on the target language side (stringto-tree).This is a new and clean way to integrate soft source syntactic constraints into string-to-tree systems as features of the rule selection model.We release our implementation as part of Moses.