Applying Statistical Post-Editing to English-to-Korean Rule-based Machine Translation System

Conventional rule-based machine translation system suffers from its weakness of fluency in the view of target language generation. In particular, when translating English spoken language to Korean, the fluency of translation result is as important as adequacy in the aspect of readability and understanding. This problem is more severe in language pairs such as English-Korean. It’s because English and Korean belong to different language family. So they have distinct characteristics. And this issue is very important factor which effects translation quality. This paper describes a statistical post-editing for improving the fluency of rule-based machine translation system. Through various experiments, we examined the effect of statistical postediting for FromTo-EK 1 system which is a kind of rule-based machine translation system, for spoken language. The experiments showed promising results for translating diverse English spoken language sentences. 1 FromTo-EK is an English-to-Korean rule-based machine translation system for some various domains (patent, paper, email and messenger).