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Partial least squares for word confidence estimation in machine translation

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Partial least squares for word confidence estimation in machine translation

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dc.contributor.author González Rubio, Jesús es_ES
dc.contributor.author Navarro Cerdán, José Ramón es_ES
dc.contributor.author Casacuberta Nolla, Francisco es_ES
dc.date.accessioned 2014-09-16T15:17:07Z
dc.date.issued 2013
dc.identifier.isbn 978-3-642-38627-5
dc.identifier.issn 0302-9743
dc.identifier.uri http://hdl.handle.net/10251/39685
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38628-2_59 es_ES
dc.description.abstract We present a new technique to estimate the reliability of the words in automatically generated translations. Our approach addresses confidence estimation as a classification problem where a confidence score is to be predicted from a feature vector that represents each translated word. We describe a new set of prediction features designed to capture context information, and propose a model based on partial least squares to perform the classification. Good empirical results are reported in a large-domain news translation task. es_ES
dc.description.sponsorship Work supported by the European Union Seventh Framework Program (FP7/2007-2013) under the CasMaCat project (grants agreement no 287576), by Spanish MICINN under TIASA (TIN2009-14205-C04-02) project, and by the Generalitat Valenciana under grant ALMPR (Prometeo/2009/014). es_ES
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Pattern Recognition and Image Analysis es_ES
dc.relation.ispartofseries Lecture Notes in Computer Science;7887
dc.rights Reserva de todos los derechos es_ES
dc.subject Machine translation es_ES
dc.subject Word confidence estimation es_ES
dc.subject Statistical multivariate analysis es_ES
dc.subject Partial least squares discriminant analysis es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Partial least squares for word confidence estimation in machine translation es_ES
dc.type Capítulo de libro es_ES
dc.embargo.lift 10000-01-01
dc.identifier.doi 10.1007/978-3-642-38628-2_59
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2009-14205-C04-02/ES/Tecnicas Interactivas Y Adaptativas Para Sistemas Automaticos De Reconocimiento, Aprendizaje Y Percepcion/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/287576/EU/Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO09%2F2009%2F014/ES/Adaptive learning and multimodality in pattern recognition (Almapater)/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation González Rubio, J.; Navarro Cerdán, JR.; Casacuberta Nolla, F. (2013). Partial least squares for word confidence estimation in machine translation. En Pattern Recognition and Image Analysis. Springer Verlag (Germany). 500-508. https://doi.org/10.1007/978-3-642-38628-2_59 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://link.springer.com/chapter/10.1007/978-3-642-38628-2_59 es_ES
dc.description.upvformatpinicio 500 es_ES
dc.description.upvformatpfin 508 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 255179
dc.contributor.funder European Commission es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.description.references NIST: National Institute of Standards and Technology MT evaluation official results (November 2006), http://www.itl.nist.gov/iad/mig/tests/mt/ es_ES
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dc.description.references Berger, A.L., Pietra, V.J.D., Pietra, S.A.D.: A maximum entropy approach to natural language processing. Computational Linguistics 22, 39–71 (1996) es_ES
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dc.description.references Mevik, B.H., Wehrens, R., Liland, K.H.: pls: Partial Least Squares and Principal Component regression. R package version 2.3-0 (2011) es_ES
dc.description.references Callison-Burch, C., Koehn, P., Monz, C., Post, M., Soricut, R., Specia, L.: Findings of the 2012 workshop on statistical machine translation. In: Proc. of the Workshop on Statistical Machine Translation, Montréal, Canada, pp. 10–51 (June 2012) es_ES
dc.description.references Chinchor, N.: The statistical significance of the muc-4 results. In: Proceedings of the Conference on Message Understanding, pp. 30–50 (1992) es_ES


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