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Optimization of word alignment clues

Published online by Cambridge University Press:  21 September 2005

JÖRG TIEDEMANN
Affiliation:
Alfa-Informatica, University of Groningen, Groningen, The Netherlands e-mail: [email protected]

Abstract

Statistical, linguistic, and heuristic clues can be used for the alignment of words and multi-word units in parallel texts. This article describes the clue alignment approach and the optimization of its parameters using a genetic algorithm. Word alignment clues can come from various sources such as statistical alignment models, co-occurrence tests, string similarity scores and static dictionaries. A genetic algorithm implementing an evolutionary procedure can be used to optimize the parameters necessary for combining available clues. Experiments on English/Swedish bitext show a significant improvement of about 6% in F-scores compared to the baseline produced by statistical word alignment.Most of the work described in this paper was carried out at the Department of Linguistics and Philology at Uppsala University. I would like to acknowledge technical and scientific support by people at the department in Uppsala.

Type
Papers
Copyright
2005 Cambridge University Press

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