Reordering for Chinese-Mongolian SMT Based on Small Parallel Corpus
Le Chen · Zhongwen xinxi xuebao · 2013
The reordering models are significant in reducing the difference of word orders between the language pairs in statistical machine translation.Most reordering approaches have high requirements of the scale of the parallel corpus in statistical machine translation.Chinese minority language resources are very scarce and difficult to achieve substantial growth in a short time.Therefore the current reordering approaches cannot play good effect in the translations between Chinese and minority languages.After analyzing the related studies,the paper proposes a sourceside reordering method based on a small parallel corpus.In virtue of the linguistic knowledge,we analyzed both corpus and translations to obtain the verb phrases which affected the word orders of translations evidently.And then we studied the reordering rules of these verb phrases,including manually written rules and automatically extracted rules.Experiments show that our method can improve the performance of the state-of-the-art phrase translation models.