PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Long-distance reordering during search for hierarchical phrase-based SMT
Fabienne Braune, Anita Gojun and Alexander Fraser
In: EAMT 2012, 28-30 May 2012, Trento, Italy.


Long-distance reordering of syntactically divergent language pairs is a critical problem. SMT has had limited success in handling these reorderings during inference, and thus deterministic preprocessing based on reordering parse trees is used. We consider German-to-English translation using Hiero. We show how to effectively model long-distance reorderings during search. Our work is novel in that we look at reordering distances of up to 50 words, and conduct a detailed manual analysis based on a new gold standard.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:9541
Deposited By:Alexander Fraser
Deposited On:02 June 2012