UWEE Tech Report Series

Leveraging Multiple Languages to Improve Statistical MT Word Alignments


UWEETR-2005-0009

Author(s):
Karim Filali, Jeff Bilmes

Keywords:
Word alignments, Machine translation, Multilingual processing, Natural Language Processing

Abstract

This is an extended version of a paper with the same title published in ASRU, 2005. We present a new multilingual statistical MT word alignment model based on a simple extension of the IBM and HMM Models and a two-step alignment procedure. Preliminary results on a small hand-aligned subset of the Europarl corpus show a 7\% relative improvement over a state of the art alignment model.

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