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This thesis investigates the influence of linguistic structure in statistical machine translation. We develop a word reordering model based on syntactic parse trees and address the issues of pronouns and morphological agreement with a source discriminative word lexicon predicting the translation for individual words using structural features. When used in phrase-based machine translation, the models improve the translation for language pairs with different word order and morphological variation.
ddc:004, Translation, Machine, DATA processing & computer science, Structure, Statistical, Linguistic, 410, info:eu-repo/classification/ddc/004, 400, 004
ddc:004, Translation, Machine, DATA processing & computer science, Structure, Statistical, Linguistic, 410, info:eu-repo/classification/ddc/004, 400, 004
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
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influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
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