MOSES를 이용한 한/일 양방향 통계기반 자동 번역 시스템
A Bidirectional Korean-Japanese Statistical Machine Translation System by Using MOSES
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참고문헌
키워드
초록
통계기반 자동 번역 시스템은 구현과 유지보수의 용이함으로 최근 많은 관심을 받고 있다. 본 연구의 목적은 MOSES[1] 시스템을 이용하여 통계기반의 한/일 양방향 기계번역시스템을 구축하는 것이다. 한/일 문장단위 병렬 코퍼스를 구축하여 번역모델 학습에 이용하였고, 한/일 각각 대량의 원시 코퍼스를이용하여 언어모델 학습에 이용하였다. 시스템 구축 결과 기존의 규칙기반 번역 시스템의 성능에 근접하는 결과를 얻었으며, 발생하는 오류의 대부분은 각 처리 단계에서 발생하는 노이즈에 기인하였다.
Abstract
Recently, statistical machine translation (SMT) has received many attention with ease of its implementation and maintenance. The goal of our works is to build bidirectional Korean-Japanese SMT system by using MOSES [1] system. We use Korean-Japanese bilingual corpus which is aligned per sentence to train the translation model and use a large raw corpus in each language to train each language model. The proposed system shows results comparable to those of a rule-based machine translation system. Most of errors are caused by noises occurred in each processing stage.
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