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Academic Paper

Title: Optimization of word alignment clues
Author: Jörg Tiedemann
Email: click here TO access email
Institution: University of Uppsala
Linguistic Field: Text/Corpus Linguistics
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.


This article appears IN Natural Language Engineering Vol. 11, Issue 3, which you can READ on Cambridge's site or on LINGUIST .

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