Bootstrapping Phrase-based Statistical Machine Translation via WSD Integration
Hien Vu Huy, Phuong-Thai Nguyen, Tung Lam Nguyen, Minh-Thuan Nguyen · International Joint Conference on Natural Language Processing · 2013
Beside the word order problem, word choice is another major obstacle for machine translation. Though phrase-based statistical machine translation (SMT) has an advantage of word choice based on local context, exploiting larger context is an interesting research topic. Recently, there have been a number of studies on integrating word sense disambiguation (WSD) into phrase-based SMT. The WSD score has been used as a feature of translation. In this paper, we will show that by bootstrapping WSD models using unlabeled data, we can bootstrap an SMT system. Our experiments on English-Vietnamese translation showed that BLEU scores have been improved significantly.