Improving Word Alignment with Bridge Languages

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 simple method for utilizing a bridge language to create a word alignment system and a procedure for combining word alignment systems from multiple bridge languages. The final translation is obtained by consensus decoding that combines hypotheses obtained using all bridge language word alignments. We present experiments showing that multilingual, parallel text in Spanish, French, Russian, and Chinese can be utilized in this framework to improve translation performance on an Arabic-to-English task.

• Type: Conference
• Year: 2007
• Where: EMNLP
• Authors: Shankar Kumar, Franz Josef Och, Wolfgang Macherey
• Keywords: Bridge Language, EMNLP 2007, Natural Language Processing, Word Alignment Systems, Word Alignments