The Improvement of Automatic Machine Translation Evaluation

Evaluation plays a critical role in the machine translation. The research of automatic machine translation evaluation is an urgent need for the natural language processing researchers and developers. This paper briefly describes the background of evaluation of machine translation and two important technology of automatic evaluation: BLEU and NIST metrics. Then, we presents some improvements for these metrics by the ideas from text retrieval, which is called TFIDF weighted metric. This method avoids the shortcoming of BLEU metric and achieves a higher F ratio value. As a result, it can give a remarkable effect on the automatic evaluation of machine translation. We also describe an evaluation platform which can take more convenience to the researches and developers.