Dependency-based Pre-ordering For English-Vietnamese Statistical Machine Translation

Abstract

Reordering is a major challenge in machine translation (MT) between two languages with significant differences in word order. In this paper, we present an approach as pre-processing step based on a dependency parser in phrase-based statistical machine translation (SMT) to learn automatic and manual reordering rules from English to Vietnamese. The dependency parse tree and transformation rules are used to reorder the source sentences and applied for systems translating English to Vietnamese. We evaluated our approach and compared on English-Vietnamese machine translation tasks, and showed that it outperforms the baseline phrase-based SMT system.