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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 Topic models for translation quality estimation for gisting purposes Rubino, Raphael; de Souza, Jose; Foster, Jennifer... In: Rubino, Raphael, de Souza, Jose, Foster, Jennifer orcid:0000-0002-7789-4853 and Specia, Lucia (2013) Topic models for translation quality estimation for gisting purposes. In: MT Summit XIV, 2-6 Sept. 2013, Nice, France. (2013) BASE Show details 2 DCU-Symantec at the WMT 2013 Quality Estimation Shared Task Wagner, Joachim; Hollowood, Fred; Foster, Jennifer... In: Rubino, Raphael, Wagner, Joachim orcid:0000-0002-8290-3849 , Foster, Jennifer orcid:0000-0002-7789-4853 , Roturier, Johann, Samad Zadeh Kaljahi, Rasoul and Hollowood, Fred (2013) DCU-Symantec at the WMT 2013 Quality Estimation Shared Task. In: 8th Workshop on Statistical Machine Translation, 8-9 Aug 2013, Sofia, Bulgaria. ISBN 978-1-937284-57-2 (2013) BASE Show details 3 Estimating the quality of translated user-generated content Hollowood, Fred; Foster, Jennifer; Kaljahi, Rasoul Samed Zadeh; Rubino, Raphael; Roturier, Johann In: Rubino, Raphael, Foster, Jennifer orcid:0000-0002-7789-4853 , Kaljahi, Rasoul Samed Zadeh, Roturier, Johann and Hollowood, Fred (2013) Estimating the quality of translated user-generated content. In: International Joint Conference on Natural Language Processing (IJCNLP), 14-18 Oct 2013, Nagoya, Japan. (2013) Abstract: Previous research on quality estimation for machine translation has demonstrated the possibility of predicting the translation quality of well-formed data. We present a first study on estimating the translation quality of user-generated con- tent. Our dataset contains English technical forum comments which were trans- lated into French by three automatic systems. These translations were rated in terms of both comprehensibility and fidelity by human annotators. Our experiments show that tried-and-tested quality estimation features work well on this type of data but that extending this set can be beneficial. We also show that the performance of particular types of features de- pends on the type of system used to produce the translation. Keyword: Computational linguistics; Machine translating; Quality estimation URL: http://doras.dcu.ie/19960/ BASE Hide details

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