Statistical machine translation model with meta-structure alignments

To deal with the structure divergence and introduce syntactic knowledge into statistical machine translation, firstly, some definitions of meta-structure, concomitancy-sequence, and reconstructed-structure were presented for the parse tree. Alignments based on different levels could be acquired with the mapping proposed. A novel translation model based on these definitions was presented in the theory of log-linear model. During the process of translation, the parse tree was decomposed, reconstructed and transformed into the target ones. Experiment shows that generative ability and translation results of this model outperform the baseline.