SMT Systems in the University of Tokyo for NTCIR-9 PatentMT
Xianchao Wu, Takuya Matsuzaki, Jun’ichi Tsujii · NTCIR · 2011
In this paper, we present two Statistical Machine Translation (SMT) systems and the evaluation results of Tsujii Labora- tory in the University of Tokyo (UOTTS) for the NTCIR-9 patent machine translation tasks (PatentMT). This year, we participated in all the three subtasks: bidirectional English- Japanese translations and Chinese-to-English translation. Our first system is a forest-to-string system making use of HPSG forests of source English sentences. We used this sys- tem to translate English forests into Japanese. The second system is a re-implementation of a hierarchical phrase based system. We applied this system to all the three subtasks. We describe the training and decoding processes of the two systems and report the translation accuracies of our systems on the official development/test sets.