The TALP-UPC phrase-based translation systems for WMT13: system combination with morphology generation, domain adaptation and corpus filtering

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/26821

dc.contributor	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.contributor	Universitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.contributor	Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.contributor	Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
dc.contributor.author	Formiga Fanals, Lluís
dc.contributor.author	Ruiz Costa-Jussà, Marta
dc.contributor.author	Mariño Acebal, José Bernardo
dc.contributor.author	Rodríguez Fonollosa, José Adrián
dc.contributor.author	Barrón-Cedeño, Alberto
dc.contributor.author	Màrquez Villodre, Lluís
dc.date	2013
dc.identifier.citation	Formiga, L. [et al.]. The TALP-UPC phrase-based translation systems for WMT13: system combination with morphology generation, domain adaptation and corpus filtering. A: Workshop on Statistical Machine Translation. "Proceedings of the Eighth Workshop on Statistical Machine Translation". Sofia: 2013, p. 134-140.
dc.identifier.citation	978-1-937284-57-2
dc.identifier.uri	http://hdl.handle.net/2117/26821
dc.language.iso	eng
dc.relation	http://www.aclweb.org/anthology/W13-2215
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
dc.subject	Speech processing systems
dc.subject	Processament de la parla
dc.title	The TALP-UPC phrase-based translation systems for WMT13: system combination with morphology generation, domain adaptation and corpus filtering
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper describes the TALP participation in the WMT13 evaluation campaign. Our participation is based on the combination of several statistical machine translation systems: based on standard hrasebased Moses systems. Variations include techniques such as morphology generation, training sentence filtering, and domain adaptation through unit derivation. The results show a coherent improvement on TER, METEOR, NIST, and BLEU scores when compared to our baseline system.

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