Automatic Evaluation Method Using Dependency Parsing Model Based on Maximum Entropy

The automatic evaluation of machine translation has achieved rich results. Various evaluation methods have emerged. This paper mainly introduces the automatic evaluation method using dependency parsing model based on maximum entropy. The dependency tree reflects the relationship between words in the sentence. Therefore, we use the dependency tree corresponding to the reference and the dependency tree corresponding to the machine translation to judge the accuracy of machine translation. In our method, the dependency tree of the reference is used as the training corpus to obtain the dependency parsing model. The model is used to generate the score of the machine translation dependency tree. Maximum entropy method is used in the dependency parsing process. The experimental results show that, at the system level, the new metric based on maximum entropy dependency parsing model is effective.