Enhance Automatic Evaluation of Machine Translation by Markov Network Based Paraphrases
Zhe Weng · Zhongwen xinxi xuebao · 2015
It is a challenge to match the different expressions(words or phrases)which have the same meanings in the automatic evaluation of machine translation.Many researchers proposed to enhance the matches between the words in machine translation and in human references by extracting paraphrases from bilingual parallel corpus or comparable corpus.However,the cost of constructing the bilingual parallel corpus or the comparable corpus is high;furthermore,it is difficult to obtain a large corpus between some language pairs.In this paper,the paraphrases are extracted from the monolingual texts in the target language by constructing the Markov networks of words,and applied to improve the correlation between the results of automatic evaluation and the human judgments of machine translation.The experimental results on WMT14 Metrics task showed that the performances of the proposed approach of extracting paraphrase from monolingual text are comparable to that of extracting paraphrase from bilingual parallel corpus.