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dc.contributor.authorMohaghegh, Mahsa
dc.contributor.authorSarrafzadeh, Hossein
dc.date.accessioned2013-06-28T03:42:23Z
dc.date.available2013-06-28T03:42:23Z
dc.date.issued2012
dc.identifier.urihttps://hdl.handle.net/10652/2229
dc.description.abstractIn this paper we show that a hierarchical phrasebased translation system will outperform a classical (nonhierarchical) phrase-based system in the English-to-Persian translation direction, yet for the Persian-to-English direction, the classical phrase-based system is preferable. We seek to explain why this is so, and detail a series of translation experiments with our SMT system using various bilingual corpora each with both toolkits Moses (non-hierarchical) and Joshua (hierarchical).en_NZ
dc.language.isoenen_NZ
dc.subjectstatistical machine translation (SMT)en_NZ
dc.subjectnatural language processingen_NZ
dc.subjecthierarchical phrase-based modelsen_NZ
dc.titleA Hierarchical Phrase-Based Model for English-Persian Statistical Machine Translationen_NZ
dc.typeConference Contribution - Paper in Published Proceedingsen_NZ
dc.rights.holderAuthorsen_NZ
dc.identifier.doi10.1109/INNOVATIONS.2012.6207733en_NZ
dc.subject.marsden089999 Information and Computing Sciences not elsewhere classifieden_NZ
dc.identifier.bibliographicCitationMohaghegh, M., and Sarrafzadeh, H. (2012). A Hierarchical Phrase-Based Model for English-Persian Statistical Machine Translation. Innovations 12, 8th International Conference on Innovations in Information Technology. 18-20 March. pp. 205-208. doi: 10.1109/INNOVATIONS.2012.6207733.en_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.conference.title8th International Conference on Innovations in Information Technologyen_NZ
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
dc.contributor.affiliationMassey Universityen_NZ
unitec.identifier.roms53244
unitec.institution.studyareaComputing


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