Lattice-based System Combination for Statistical Machine Translation

Current system combination methods usually use confusion networks to find consensus translations among different systems. Requiring one-to-one mappings between the words in candidate translations, confusion networks have difficulty in handling more general situations in which several words are connected to another several words. Instead, we propose a lattice-based system combination model that allows for such phrase alignments and uses lattices to encode all candidate translations. Experiments show that our approach achieves significant improvements over the state-ofthe-art baseline system on Chinese-to-English translation test sets.

• Type: Journal
• Year: 2009
• Where: EMNLP
• Authors: Yang Feng, Yang Liu, Haitao Mi, Qun Liu, Yajuan Lü
• Keywords: Candidate Translations, Confusion Networks, EMNLP 2009, Natural Language Processing, Translation Test Sets