The customyzation of neural machine translation with user's dictionary

Abstract

Neural machine translation (NMT) has significantly improved quality over traditional statistical-based machine translation (SMT). However, it is known that it is difficult for NMT to translate sentences containing rare terms. Therefore, in this research, we propose a method of replacing rare terms with synonyms and translating it, and replacing the translated synonyms with translations of the rare terms in the bilingual dictionary. This approach has two technical issues: acquisition of synonyms from small scale corpus, and selection of the synonyms. The proposed method shows the better result than the result of the existing technics in sign test.