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.

本文介绍了基于 Tree-to-String 模型的重新排序系统，并使用公开工具来完成任务。我们使用 Moses 工具包构建了翻译模型，然后应用 Moses 中的 Chart Decoder 对句子进行重新排序。通过实验发现，该方法在不同语言对组合中的 BLEU、Kendall-Tau 和 Hamming 指标上均有显著改善，同时提出了进一步改进的可能方向。