Improving automatic Chinese-Japanese patent translation using bilingual term extraction

Wei Yang*, Yves Lepage

*この研究の対応する著者

研究成果: Article査読

抄録

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.

本文言語English
ジャーナルIEEJ Transactions on Electrical and Electronic Engineering
DOI
出版ステータスAccepted/In press - 2017

ASJC Scopus subject areas

  • 電子工学および電気工学

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