ISBN: 9783639145502 - distortion constraints in statistical machine translation: constraining word reordering in machine translation with rules and knowledge outside of the statistical mt model (16 resultados)

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Taschenbuch. Condición: Neu. Distortion Constraints in Statistical Machine Translation | Constraining word reordering in Machine Translation with rules and knowledge outside of the Statistical MT model | Marian Gelu Olteanu | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639145502 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.…

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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Olteanu Marian GeluMarian Gelu Olteanu was born on October 30, 1978 in Pitesti, nRomania. Marian attended Politehnica University of Bucharest nwhere he received his B.S. in Computer nScience in 2002. He also attended The University o.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Statistical machine translation (SMT) offers many benefits over rule based and example based machine translation especially ease to train and robustness. It represents state-of-the-art in machine translation (MT) but it has to deal with certain issues that are not trivial to solve in a statistical framework: correct distortion, correct agreement, morphology issues, etc. In order to solve distortion issues, different models were proposed: syntax-based MT, enhanced distortion models, clause restructuring. All of these define more complex distortion models than monotonic distortion models (which favor lack of word reordering). These proposed models don't completely solve the issue of easily adding linguistic knowledge into the MT decoder. The work proposes a model designed to augment SMT models with linguistic knowledge, either in a rule-based fashion or in a probabilistic fashion. The theoretical framework proposed in this work was implemented in Phramer statistical phrase-based decoder and tested using various levels of knowledge - surface , partof speech, constituency parse trees. The experimental results show improvement in the quality of the translation.…

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