Improving automatic Chinese–Japanese patent translation using bilingual term extraction

Abstract

The identification of terms in scientific and patent documents is a crucial issue for applications like information retrieval, text categorization, and also for machine translation. This paper describes a method to improve Chinese–Japanese statistical machine translation of patents by re‐tokenizing the training corpus with aligned bilingual multi‐word terms. We automatically extract multi‐word terms from monolingual corpora by combining statistical and linguistic filtering methods. An automatic alignment method is used to identify corresponding terms. The most promising bilingual multi‐word terms are extracted by setting some threshold on translation probabilities and further filtering by considering the components of the bilingual multi‐word terms in characters as well as the ratio of their lengths in words. We also use kanji (Japanese)–hanzi (Chinese) character conversion to confirm and extract more promising bilingual multi‐word terms. We obtain a high quality of correspondence with 93% in bilingual term extraction and a significant improvement of 1.5 BLEU score in a translation experiment. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.