Towards a discourse relation-aware approach for Chinese-English machine translation

Abstract

Translation of discourse relations is one of the recent efforts of incorporating discourse information to statistical machine translation (SMT). While existing works focus on disambiguation of ambiguous discourse connectives, or transformation of discourse trees, only explicit discourse relations are tackled. A greater challenge exists in machine translation of Chinese, since implicit discourse relations are abundant and occur both inside and outside a sentence. This thesis proposal describes ongoing work on bilingual discourse annotation and plans towards incorporating discourse relation knowledge to a ChineseEnglish SMT system with consideration of implicit discourse relations. The final goal is a discourse-unit-based translation model unbounded by the traditional assumption of sentence-to-sentence translation.