Academic Paper |
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| Title: | Optimization of word alignment clues |
| Author: | Jörg Tiedemann |
| Email: | click here to access email |
| Homepage: | http://www.let.rug.nl/~tiedeman |
| Institution: | University of Groningen |
| 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. |
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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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