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Discriminative ridge regression algorithm for adaptation in statistical machine translation

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Discriminative ridge regression algorithm for adaptation in statistical machine translation

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dc.contributor.author Chinea-Ríos, Mara es_ES
dc.contributor.author Sanchis-Trilles, Germán es_ES
dc.contributor.author Casacuberta Nolla, Francisco es_ES
dc.date.accessioned 2020-12-19T04:32:01Z
dc.date.available 2020-12-19T04:32:01Z
dc.date.issued 2019-11 es_ES
dc.identifier.issn 1433-7541 es_ES
dc.identifier.uri http://hdl.handle.net/10251/157503
dc.description.abstract [EN] We present a simple and reliable method for estimating the log-linear weights of a state-of-the-art machine translation system, which takes advantage of the method known as discriminative ridge regression (DRR). Since inappropriate weight estimations lead to a wide variability of translation quality results, reaching a reliable estimate for such weights is critical for machine translation research. For this reason, a variety of methods have been proposed to reach reasonable estimates. In this paper, we present an algorithmic description and empirical results proving that DRR is able to provide comparable translation quality when compared to state-of-the-art estimation methods [i.e. MERT and MIRA], with a reduction in computational cost. Moreover, the empirical results reported are coherent across different corpora and language pairs. es_ES
dc.description.sponsorship The research leading to these results were partially supported by projects CoMUN-HaT-TIN2015-70924-C2-1-R (MINECO/FEDER) and PROMETEO/2018/004. We also acknowledge NVIDIA for the donation of a GPU used in this work. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Pattern Analysis and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Statistical machine translation es_ES
dc.subject Log-linear model es_ES
dc.subject Discriminative ridge regression algorithm es_ES
dc.subject Log-linear weights es_ES
dc.subject Adaptation es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Discriminative ridge regression algorithm for adaptation in statistical machine translation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10044-018-0720-5 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2018%2F004/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-70924-C2-1-R/ES/CONTEXTO, MULTIMODALIDAD Y COLABORACION DEL USUARIO EN PROCESADO DE TEXTO MANUSCRITO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2019%2F121/ES/Deep learning for adaptative and multimodal interaction in pattern recognition/ es_ES
dc.rights.accessRights Abierto 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 Chinea-Ríos, M.; Sanchis-Trilles, G.; Casacuberta Nolla, F. (2019). Discriminative ridge regression algorithm for adaptation in statistical machine translation. Pattern Analysis and Applications. 22(4):1293-1305. https://doi.org/10.1007/s10044-018-0720-5 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10044-018-0720-5 es_ES
dc.description.upvformatpinicio 1293 es_ES
dc.description.upvformatpfin 1305 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 22 es_ES
dc.description.issue 4 es_ES
dc.relation.pasarela S\362954 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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