Machine translation system for patent documents combining rule-based translation and statistical post-editing applied to the PatentMT Task

In this article, we describe system architecture, preparation of training data and experimental results of the EIWA group in the NTCIR-9 Patent Translation Task. Our system is combining rulebased machine translation and statistical post-editing. Experimental results for Japanese to English (JE) subtask show 0.3169 BLEU score, 7.8161 NIST score, 0.7404 RIBES score, 3.43 adequacy score and 0.6381 pair wise comparison score for acceptability. Experimental results for Chinese to English (CE) subtask show 0.2597 BLEU score, 7.2282 NIST score, 0.7455 RIBES score, and 3.05 adequacy score.