OpenE:an Automatic Method of MT Evaluation Based on N-gram Co-occurrence
Tianshun Yao · Zhongwen xinxi xuebao · 2004
Evaluations are very helpful for the research of Machine Translation (MT). The aim of evaluations is not only to output the differences among MT systems, but also to stimulate the improvement of key technologies in this area. In the past, the evaluations of MT are performed by human. With the increasing needs of MT research, the automatization of MT evaluations becomes more and more important. This paper introduces the basic framework of automatic MT evaluation using n-gram co-occurrence statistics. Three methods (BLEU, NIST and OpenE) based on this framework are described. The advantages and disadvantages of these methods are also discussed through the analysis of several experiments. Among these methods, OpenE adopts a new method of n-gram weighting which employs a local corpus and a large global corpus. Through the experiments, this method is proved to be practical for machine translation evaluation.