Paper: Improving Word Alignment with Bridge Languages

ACL ID D07-1005
Title Improving Word Alignment with Bridge Languages
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007

We describe an approach to improve Statistical Machine Translation (SMT) performance using multi-lingual, parallel, sentence-aligned corpora in several bridge languages. Our approach consists of a sim- ple method for utilizing a bridge language to create a word alignment system and a proce- dure for combining word alignment systems from multiple bridge languages. The final translation is obtained by consensus de- coding that combines hypotheses obtained using all bridge language word alignments. We present experiments showing that mul- tilingual, parallel text in Spanish, French, Russian, and Chinese can be utilized in this framework to improve translation performance on an Arabic-to-English task.