Paper: Reordering Modeling using Weighted Alignment Matrices

ACL ID P11-2079
Title Reordering Modeling using Weighted Alignment Matrices
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011

In most statistical machine translation sys- tems, the phrase/rule extraction algorithm uses alignments in the 1-best form, which might contain spurious alignment points. The usage of weighted alignment matrices that encode all possible alignments has been shown to gener- ate better phrase tables for phrase-based sys- tems. We propose two algorithms to generate the well known MSD reordering model using weighted alignment matrices. Experiments on the IWSLT 2010 evaluation datasets for two language pairs with different alignment algo- rithms show that our methods produce more accurate reordering models, as can be shown by an increase over the regular MSD models of 0.4 BLEU points in the BTEC French to English test set, and of 1.5 BLEU points in the DIALOG Chinese to English test set.