论文信息 - Comparing Reordering Constraints for SMT Using Efficient BLEU Oracle Computation

Comparing Reordering Constraints for SMT Using Efficient BLEU Oracle Computation

This paper describes a new method to compare reordering constraints for Statistical Machine Translation. We investigate the best possible (oracle) Bleu score achievable under different reordering constraints. Using dynamic programming, we efficiently find a reordering that approximates the highest attainable Bleu score given a reference and a set of reordering constraints. We present an empirical evaluation of popular reordering constraints: local constraints, the IBM constraints, and the Inversion Transduction Grammar (ITG) constraints. We present results for a German-English translation task and show that reordering under the ITG constraints can improve over the baseline by more than 7.5 Bleu points.

Sanjeev Khudanpur | Markus Dreyer | Keith B. Hall | S. Khudanpur | Markus Dreyer

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