Paper: Improving Pivot-Based Statistical Machine Translation Using Random Walk

ACL ID D13-1050
Title Improving Pivot-Based Statistical Machine Translation Using Random Walk
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

This paper proposes a novel approach that uti- lizes a machine learning method to improve pivot-based statistical machine translation (SMT). For language pairs with few bilingual data, a possible solution in pivot-based SMT using another language as a "bridge" to gen- erate source-target translation. However, one of the weaknesses is that some useful source- target translations cannot be generated if the corresponding source phrase and target phrase connect to different pivot phrases. To allevi- ate the problem, we utilize Markov random walks to connect possible translation phrases between source and target language. Experi- mental results on European Parliament data, spoken language data and web data show that our method leads to significant improvements on all the tasks over ...