A Linguistically Annotated Reordering Model for BTG-based Statistical Machine Translation

In this paper, we propose a linguistically annotated reordering model for BTG-based statistical machine translation. The model incorporates linguistic knowledge to predict orders for both syntactic and non-syntactic phrases. The linguistic knowledge is automatically learned from source-side parse trees through an annotation algorithm. We empirically demonstrate that the proposed model leads to a sig

• Type: Conference
• Year: 2008
• Where: ACL
• Authors: Deyi Xiong, Min Zhang, AiTi Aw, Haizhou Li
• Keywords: ACL 2008, BTG-based Statistical Machine, Computational Linguistics, Linguistic Knowledge, Model