Overview of Tree-to-String Translation Models

  • Yang Liu | Institute of Computing Technology, Chinese Academy of Sciences

Recent research on statistical machine translation has lead to the rapid development of syntax-based translation models, which exploit syntactic information to direct translation. In this talk, I will give an overview of tree-to-string translation models, one of the state-of-the-art syntax-based models. In a tree-to-string model, the source side is a phrase structure parse tree and the target side is a string. This talk includes the following topics: (1) tree-based tree-to-string model, (2) tree-sequence based tree-to-string model, (3) forest-based tree-to-string model, and (4) context-aware tree-to-string model. Experimental results show that the forest-based tree-to-string system outperforms Hiero significantly on Chinese-to-English translation.

Speaker Details

Yang Liu is an Assistant Researcher at Institute of Computing Technology (ICT), Chinese Academy of Sciences. He received his PhD degree in Computer Science from ICT in 2007. His major research interests include statistical machine translation and Chinese information processing. He has been working on syntax-based modeling, word alignment, and system combination. His paper on tree-to-string translation won the Meritorious Asian NLP Paper Award of COLING/ACL 2006. He served as Reviewers for TALIP, TSLP, JNLE, ACL, EMNLP, AMTA, and SSST.

Watch Next