A Probabilistic Approach to Syntax-based Reordering for Statistical Machine Translation

Inspired by previous preprocessing approaches to SMT, this paper proposes a novel, probabilistic approach to reordering which combines the merits of syntax and phrase-based SMT. Given a source sentence and its parse tree, our method generates, by tree operations, an n-best list of reordered inputs, which are then fed to standard phrase-based decoder to produce the optimal translation. Experiments show that, for the NIST MT-05 task of Chinese-toEnglish translation, the proposal leads to

• Type: Conference
• Year: 2007
• Where: ACL
• Authors: Chi-Ho Li, Minghui Li, Dongdong Zhang, Mu Li, Ming Zhou, Yi Guan
• Keywords: ACL 2007, Computational Linguistics, NIST MT-05 Task, Phrase-based Decoder, Phrase-based Smt