Improving Word Alignment with Bridge Languages
Venue
Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Association for Computational Linguistics, 209 N. Eighth Street, East Stroudsburg, PA, USA (2007)
Publication Year
2007
Authors
Shankar Kumar, Franz Och, Wolfgang Macherey
BibTeX
Abstract
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.
