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In this paper, we propose a novel BTG-forest-based alignment method. Based ona fast unsupervised initialization of parameters using variational IBM models,we synchronously parse parallel sentences top-down and align hierarchicallyunder the constraint of BTG. Our two-step method can achieve the same run-timeand comparable translation performance as fast_align while it yields smallerphrase tables. Final SMT results show that our method even outperforms in theexperiment of distantly related languages, e.g., English-Japanese.

Fast BTG-Forest-Based Hierarchical Sub-sentential Alignment