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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 – 5 of 5 1 Predicting sentence translation quality using extrinsic and language independent features Groves, Declan; van Genabith, Josef; Bicici, Ergun In: Bicici, Ergun, Groves, Declan and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) Predicting sentence translation quality using extrinsic and language independent features. Machine Translation, 27 (3-4). pp. 171-192. ISSN 0922-6567 (2013) Abstract: We develop a top performing model for automatic, accurate, and language independent prediction of sentence-level statistical machine translation (SMT) quality with or without looking at the translation outputs. We derive various feature functions measuring the closeness of a given test sentence to the training data and the difficulty of translating the sentence. We describe \texttt{mono} feature functions that are based on statistics of only one side of the parallel training corpora and \texttt{duo} feature functions that incorporate statistics involving both source and target sides of the training data. Overall, we describe novel, language independent, and SMT system extrinsic features for predicting the SMT performance, which also rank high during feature ranking evaluations. We experiment with different learning settings, with or without looking at the translations, which help differentiate the contribution of different feature sets. We apply partial least squares and feature subset selection, both of which improve the results and we present ranking of the top features selected for each learning setting, providing an exhaustive analysis of the extrinsic features used. We show that by just looking at the test source sentences and not using the translation outputs at all, we can achieve better performance than a baseline system using SMT model dependent features that generated the translations. Furthermore, our prediction system is able to achieve the $2$nd best performance overall according to the official results of the Quality Estimation Task (QET) challenge when also looking at the translation outputs. Our representation and features achieve the top performance in QET among the models using the SVR learning model. Keyword: Computational linguistics; Machine learning; Machine translating; Performance prediction; Quality estimation; Statistical machine translation URL: http://doras.dcu.ie/19283/ BASE Hide details 2 Feature decay algorithms for fast deployment of accurate statistical machine translation systems Bicici, Ergun In: Bicici, Ergun (2013) Feature decay algorithms for fast deployment of accurate statistical machine translation systems. In: ACL 2013 8th workshop on statistical machine translation, 8-9 Aug 2013, Sofia, Bulgaria. (2013) BASE Show details 3 CNGL: Grading student answers by acts of translation van Genabith, Josef; Bicici, Ergun In: Bicici, Ergun orcid:0000-0002-2293-2031 and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) CNGL: Grading student answers by acts of translation. In: SEMEVAL, 14-15 Jun 2013, Atlanta, Georgia. (2013) BASE Show details 4 CNGL-CORE: Referential translation machines for measuring semantic similarity van Genabith, Josef; Bicici, Ergun In: Bicici, Ergun orcid:0000-0002-2293-2031 and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) CNGL-CORE: Referential translation machines for measuring semantic similarity. In: *SEM, 13-14 Jun 2013, Atlanta, Georgia. (2013) BASE Show details 5 Referential translation machines for quality estimation Bicici, Ergun In: Bicici, Ergun (2013) Referential translation machines for quality estimation. In: ACL 2013 8th workshop on statistical machine translation, 8-9 Aug 2013, Sofia, Bulgaria. (2013) BASE Show details

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