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dc.contributor.authorHabash, Nizaren_US
dc.contributor.authorDorr, Bonnieen_US
dc.date.accessioned2004-05-31T23:16:44Z
dc.date.available2004-05-31T23:16:44Z
dc.date.created2002-03en_US
dc.date.issued2002-04-04en_US
dc.identifier.urihttp://hdl.handle.net/1903/1185
dc.description.abstractThis paper describes a novel approach for handling translation divergences in a Generation-Heavy Hybrid Machine Translation (GHMT) system. The approach depends on the existence of rich target language resources such as word lexical semantics, including information about categorial variations and subcategorization frames. These resources are used to generate multiple structural variations from a target-glossed lexico-syntactic representation of the source language sentence. The multiple structural variations account for different translation divergences. The overgeneration of the approach is constrained by a target-language model using corpus-based statistics. The exploitation of target language resources (symbolic and statistical) to handle a problem usually reserved to Transfer and Interlingual MT is useful for translation from structurally divergent source languages with scarce linguistic resources. A preliminary evaluation on the application of this approach to Spanish-English MT proves this approach extremely promising. The approach however is not limited to MT as it can be extended to monolingual NLG applications such as summarization. Also UMIACS-TR-2002-23 Also LAMP-TR-083en_US
dc.format.extent196099 bytes
dc.format.mimetypeapplication/postscript
dc.language.isoen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4341en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2002-23en_US
dc.relation.ispartofseriesLAMP-TR-083en_US
dc.titleHandling Translation Divergences in Generation-Heavy Hybrid Machine Translationen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US


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