We identify problems with the Penn Treebank that render it imperfect for syntaxbased machine translation and propose methods of relabeling the syntax trees to improve translation quality. We develop a system incorporating a handful of relabeling strategies that yields a statistically significant improvement of 2.3 BLEU points over a baseline syntax-based system.
To improve the performance of syntactic machine translation, REF proposed a method incorporating a handful of relabeling strategies to modify the syntactic trees structures.
Relabeling Syntax Trees To Improve Syntax-Based Machine Translation Quality
Human Language Technology Conference And Meeting Of The North American Association For Computational Linguistics
Computer Science