[PDF] Top 20 UHH Submission to the WMT17 Quality Estimation Shared Task
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UHH Submission to the WMT17 Quality Estimation Shared Task
... terms of Pearson’s coefficient, albeit slightly worse on average than the tree kernels based im- plementations. This is a very important aspect, as the integration of sequence kernels into QE sys- tems does not require ... See full document
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Alibaba Submission for WMT18 Quality Estimation Task
... on WMT17 QE Task Since we can access the translation outputs of hu- man post-editing for test data, it provides an ideal held-out test data to verify our proposed ...on WMT17 QE ... See full document
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Unbabel’s Participation in the WMT19 Translation Quality Estimation Shared Task
... We present the contribution of the Unbabel team to the WMT 2019 Shared Task on Qual- ity Estimation. We participated on the word, sentence, and document-level tracks, encom- passing 3 language pairs: ... See full document
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Findings of the WMT 2018 Shared Task on Quality Estimation
... In Task 1, for English-German, the numbers of translations in the QE training data from the two systems are very different (26, 273 for SMT and 13, 442 for NMT) and thus no direct com- parison can be ...higher ... See full document
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FBK UEdin Participation to the WMT13 Quality Estimation Shared Task
... In the official results released by the organiz- ers our submissions had close performances for Task 1.1. The difference between the SVR and the extremely randomized tree models is very small (around 0.0012 MAE ... See full document
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The UU Submission to the Machine Translation Quality Estimation Task
... This paper outlines the UU-SVM system for Task 1 of the WMT16 Shared Task in Quality Estimation. Our system uses Sup- port Vector Machine Regression to investi- gate the impact of a ... See full document
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Bilexical Embeddings for Quality Estimation
... ity Estimation shared task of WMT17, namely: (i) a word-level prediction sys- tem using bilexical embeddings, (ii) a phrase-level labelling approach based on the word-level predictions, (iii) ... See full document
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YSDA Participation in the WMT’16 Quality Estimation Shared Task
... (YSDA) submission for WMT2016 Shared Task on Quality Esti- mation (QE) / Task 1: Sentence-level pre- diction of post-editing ...of quality estimation by using a machine ... See full document
7
DCU Symantec Submission for the WMT 2012 Quality Estimation Task
... We presented in this paper our submission for the WMT12 Quality Estimation shared task. We also presented further experiments using different ma- chine learning techniques and we ... See full document
7
Sheffield Submissions for the WMT18 Quality Estimation Shared Task
... For this year’s shared task, post-edited (PE) and manually annotated data were provided. They cover four levels of predictions: sentence-level (task 1), word-level (task 2), phrase-level ... See full document
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Black Box Features for the WMT 2012 Quality Estimation Shared Task
... our submission to the WMT 2012 quality estimation (QE) shared ...the task is to build a predic- tor that can accurately estimate the quality of fur- ther ... See full document
5
NJU Submissions for the WMT19 Quality Estimation Shared Task
... QE task and these neural ap- proaches have shown promising ...QE task, which does not require manual effort for finding the best relevant ...the WMT17 sentence-level QE task on English-German ... See full document
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UGENT LT3 SCATE Submission for WMT16 Shared Task on Quality Estimation
... (MT) Quality Estimation (QE) is the task of providing a quality indicator for unseen automatically translated sentences without relying on reference translations (Gandrabur and Foster, 2003; ... See full document
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Unbabel’s Participation in the WMT17 Translation Quality Estimation Shared Task
... We use the pure quality estimation system devel- oped by the Unbabel team and described in Mar- tins et al. (2017), which consists of an ensemble of a linear feature-based classifier with a neural network. ... See full document
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The UPC Submission to the WMT 2012 Shared Task on Quality Estimation
... To extract the extended feature set we use an align- ment model, a POS tagger and a dependency parser. Concerning the former, we trained an unsupervised model with the Berkeley aligner 4 , an implementa- tion of the ... See full document
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UHH Submission to the WMT17 Metrics Shared Task
... and the back-translation respectively and s mark- ing the source segment. Our rationale for utilizing the pseudo-reference was motivated by two fac- tors. In the first place, we wanted to determine whether an additional ... See full document
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LCT MALTA’s Submission to RepEval 2017 Shared Task
... 2017 Shared Task aims to evalu- ate fixed-length vector representations (or embed- dings) of sentences on the basis of a natural lan- guage understanding task, ...classification task at ... See full document
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AX Semantics’ Submission to the SIGMORPHON 2019 Shared Task
... Our two systems represent our learning curve in the attempt to solve the given shared task. The first system is a solution entirely based on given AllenNLP components. The second system has a custom trainer ... See full document
5
CUNI submission in WMT17: Chimera goes neural
... The common components for all the tested sys- tems are language models, which were taken from CUNI’s last year submission. For some experi- ments we have used up to 4 phrase tables sepa- rately as Moses ... See full document
9
DCU Symantec at the WMT 2013 Quality Estimation Shared Task
... We presented in this paper our experiments for the WMT13 Quality Estimation shared task. Our ap- proach is based on the extraction of a large ini- tial feature set, followed by two feature ... See full document
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