Wider context by using bilingual language models in machine translation

Abstract

In past Evaluations for Machine Translation of European Languages, it could be shown that the translation performance of SMT systems can be increased by integrating a bilingual lan- guage model into a phrase-based SMT system. In the bilingual language model, target words with their aligned source words build the tokens of an n-gram based language model. We analyzed the effect of bilingual language models and show where they could help to bet- ter model the translation process. We could show improvements of translation quality on German-to-English and Arabic-to-English. In addition, for the Arabic-to-English task, train- ing an extra bilingual language model on the POS tags instead of the surface word forms led to further improvements.