Improving Word Alignment with Bridge Languages
Shankar Kumar, Franz Josef Och, Wolfgang Macherey · 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. 1