Building a reordering system using tree-to-string hierarchical model

This paper describes our submission to the First Workshop on Reordering for Statistical Machine Translation. We have decided to build a reordering system based on tree-to-string model, using only publicly available tools to accomplish this task. With the provided training data we have built a translation model using Moses toolkit, and then we applied a chart decoder, implemented in Moses, to reorder the sentences. Even though our submission only covered English-Farsi language pair, we believe that the approach itself should work regardless of the choice of the languages, so we have also carried out the experiments for English-Italian and English-Urdu. For these language pairs we have noticed a significant improvement over the baseline in BLEU, Kendall-Tau and Hamming metrics. A detailed description is given, so that everyone can reproduce our results. Also, some possible directions for further improvements are discussed.