The RWTH Aachen System for NTCIR-10 PatentMT

This paper describes the statistical machine translation (SMT) systems developed by RWTH Aachen University for the Patent Translation task of the 10th NTCIR Workshop. Both phrase-based and hierarchical SMT systems were trained for the Japanese-English and Chinese-English tasks. Experiments were conducted to compare standard and inverse direction decoding, the performance of several additional models and the addition of monolingual training data. Moreover, for the Chinese-English subtask we applied a system combination technique to create a consensus hypothesis from several different systems