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dc.contributor.authorAvramidis, Elefterios
dc.contributor.authorRuiz Costa-Jussà, Marta
dc.contributor.authorFedermann, Christian
dc.contributor.authorMelero, Maite
dc.contributor.authorPecina, Pavel
dc.contributor.authorVan Genabith, Josef
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2017-03-14T18:21:20Z
dc.date.available2017-03-14T18:21:20Z
dc.date.issued2012
dc.identifier.citationAvramidis, E., Ruiz, M., Federmann, C., Melero, M., Pecina, P., Van Genabith, J. A Richly annotated, multilingual parallel corpus for hybrid machine translation. A: International Conference on Language Resources and Evaluation. "Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)". European Language Resources Association (ELRA), 2012, p. 2189-2193.
dc.identifier.isbn978-2-9517408-7-7
dc.identifier.urihttp://hdl.handle.net/2117/102468
dc.description.abstractIn recent years, machine translation (MT) research has focused on investigating how hybrid machine translation as well as system combination approachescan bedesigned so that theresulting hybrid translationsshow an improvement over theindividual “component” translations. As a first step towards achieving this objectivewe have developed a parallel corpuswith source text and the corresponding translation output from a number of machine translation engines, annotated with metadata information, capturing aspects of the translation process performed by the different MT systems. This corpus aims to serve as a basic resource for further research on whether hybridmachinetranslation algorithmsand systemcombination techniques can benefit fromadditional (linguistically motivated, decoding, and runtime) information provided by thedifferent systems involved. In this paper, wedescribe the annotated corpuswehave created. We provide an overview on the component MT systems and the XLIFF-based annotation format we have developed. We also report on first experimentswith theML4HMT corpus data.
dc.format.extent5 p.
dc.language.isoeng
dc.publisherEuropean Language Resources Association (ELRA)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshMachine translation
dc.subject.otherMachineTranslation
dc.subject.otherSystemCombination
dc.subject.otherAnnotated Corpus
dc.titleA Richly annotated, multilingual parallel corpus for hybrid machine translation
dc.typeConference report
dc.subject.lemacTraducció automàtica
dc.contributor.groupUniversitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.relation.publisherversionhttp://www.lrec-conf.org/proceedings/lrec2012/index.html
dc.rights.accessOpen Access
local.identifier.drac19709082
dc.description.versionPostprint (published version)
local.citation.authorAvramidis, E.; Ruiz, M.; Federmann, C.; Melero, M.; Pecina, P.; Van Genabith, J.
local.citation.contributorInternational Conference on Language Resources and Evaluation
local.citation.publicationNameProceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)
local.citation.startingPage2189
local.citation.endingPage2193


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