Statistical machine translation enhancements through linguistic levels: a survey
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- dc.contributor.author Costa-jussà, Marta R.ca
- dc.contributor.author Farrús, Mireiaca
- dc.date.accessioned 2018-05-09T15:30:57Z
- dc.date.available 2018-05-09T15:30:57Z
- dc.date.issued 2014
- dc.description.abstract Machine translation can be considered a highly interdisciplinary and multidisciplinary field because it is approached from the point of view of human translators, engineers, computer scientists, mathematicians and linguists. One of the most popular approaches is the statistical machine translation (SMT) approach which tries to cover translation in a holistic manner by learning from parallel corpus aligned at the sentence level. However, with this basic approach, there are some issues at each written linguistic level (i.e. orthographic, morphological, lexical, syntactic and semantic) that remain unsolved. Research in SMT has continuously been focused on solving the different linguistic levels challenges. This paper represents a survey of how the SMT has been enhanced to perform translation correctly at all linguistic levels.en
- dc.description.sponsorship This work is supported by the Seventh Framework Program of the European Commission through the International Outgoing Fellowship Marie Curie Action (IMTraP-2011-29951).en
- dc.format.mimetype application/pdf
- dc.identifier.citation Costa-Jussà MR, Farrús M. Statistical machine translation enhancements through linguistic levels: a survey. ACM Comput Surv. 2014; 46 (3): 42. DOI: 10.1145/2518130
- dc.identifier.doi http://dx.doi.org/10.1145/2518130
- dc.identifier.issn 0360-0300
- dc.identifier.uri http://hdl.handle.net/10230/34599
- dc.language.iso eng
- dc.publisher ACM Association for Computer Machineryca
- dc.relation.ispartof ACM Computing Survey. 2014;46(3):42.
- dc.rights © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys (CSUR), 46(3) 2014. http://doi.acm.org/10.1145/2518130
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.subject.keyword Linguisticsen
- dc.subject.keyword Statistical machine translationen
- dc.subject.keyword Orthographyen
- dc.subject.keyword Morphologyen
- dc.subject.keyword Lexisen
- dc.subject.keyword Syntaxen
- dc.subject.keyword Semanticsen
- dc.title Statistical machine translation enhancements through linguistic levels: a surveyca
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/acceptedVersion