Machine Translation Using Bilingual Term Entries Extracted From Parallel Texts

Abstract

Patent summaries are machine-translated using bilingual term entries extracted from parallel texts for evaluation. The result shows that bilingual term entries extracted from 2,000 pairs of parallel texts which share a specific domain with the input texts introduce more improvements than a technical term dictionary with 38,000 entries which covers a broader domain. The result also shows that only 10 pairs of parallel texts found by similar document retrieval have comparable effects to the technical term dictionary, suggesting that parallel texts to be used do not need to be classified into fields prior to term extraction