[PDF] Top 20 Neural Post Editing Based on Quality Estimation
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Neural Post Editing Based on Quality Estimation
... specific neural post-editing (NPE) models in term of the edit numbers, and select the best model by machine translation quality estima- tion ... See full document
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Post editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain
... been post- editing outputs of the MT systems used in the ex- periment (see above) for three months, and had re- ceived four hours of post-editing ... See full document
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Neural Automatic Post Editing Using Prior Alignment and Reranking
... Our neural model of APE is based on the work described in Cohn et ...tion based bidirectional recurrent neural network (RNN) MT model (Bahdanau et ...performing neural APE ... See full document
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Estimating Grammar Correctness for a Priori Estimation of Machine Translation Post Editing Effort
... Previous quality estimation meth- ods differ in nature from the presented view, given that they attempt to predict a discrete level of post- editing effort (Bojar et ...WMT Quality ... See full document
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An Exploration of Neural Sequence to Sequence Architectures for Automatic Post Editing
... ble 1 summarizes the data sets used in this work. To produce our final training data set we over- sample the original training data 20 times and add both artificial data sets. This results in a total of slightly more ... See full document
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Pre editing Plus Neural Machine Translation for Subtitling: Effective Pre editing Rules for Subtitling of TED Talks
... are based on the previous research and are intended to be as simple and easy to follow as possible, so they can be used by monolingual users with limited knowledge of ...NMT quality of TED Talk subtitling? ... See full document
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Japanese to English/Chinese/Korean Datasets for Translation Quality Estimation and Automatic Post Editing
... Reference translations were manually given, refer- ring only to the source segments (src). As each src was not attributed with its specific context, we asked the translators to imagine some context as long as it is ... See full document
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Effort Aware Neural Automatic Post Editing
... were based on Transformer (Vaswani et ...in neural MT (NMT), with two encoders to encode both source text and MT ...to post- edit the output of Phrase-Based Statistical Ma- chine Translation ... See full document
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Adaptive HTER Estimation for Document Specific MT Post Editing
... ity estimation that predicts sentence-level human- targeted translation error rate (HTER) (Snover et ...MT post-editing system. HTER is an ideal quality measurement for MT post ... See full document
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Neural based Post Processing Filtering Technique for Image Quality Enhancement
... A Neural Based Post Processing Technique for Image Quality Enhancement (NBPPTIQE) for enhancing digital images corrupted by impulse noise is proposed in this ...Adaptive Neural (FAN) ... See full document
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Recurrent Neural Network based Translation Quality Estimation
... The cause of these separated parts of the QE model comes from the insufficiency of QE datasets to train the whole QE model. Thus, the QE model is divided into two parts, and then different training data are used to train ... See full document
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The Impact of Machine Translation Quality on Human Post Editing
... the quality increases measured by auto- matic metrics and subjective evaluation criteria re- late to actual increases in the productivity of post- editors is still an open research ...for ... See full document
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Raising the TM Threshold in Neural MT Post Editing: a Case Study onTwo Datasets
... MT quality in general with the spread of neural MT ...use neural MT for the ...the editing time and the sub- jective quality perception of the ...of editing, but does not im- ... See full document
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Keep It or Not: Word Level Quality Estimation for Post Editing
... estimating quality of a machine translation (MT) system without referring the ac- tual translation is now one of the key research ar- eas in MT domain (Blatz et ...document quality estimation can be ... See full document
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A Neural Network based Approach to Automatic Post Editing
... Translations provided by state-of-the-art MT systems suffer from a number of errors including incorrect lexical choice, word ordering, word in- sertion, word deletion, etc. The APE work pre- sented in this paper is an ... See full document
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Fine grained evaluation of Quality Estimation for Machine translation based on a linguistically motivated Test Suite
... Ondej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, ... See full document
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Automatic Post Editing and Machine Translation Quality Estimation at eBay
... Proceedings for AMTA 2018 Workshop: Translation Quality Estimation and Automatic Post-Editing Boston, March 21, 2018 | Page 1.. Nicola Ueffing • Research scientist on eBay‘s machine tran[r] ... See full document
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Ensembling Factored Neural Machine Translation Models for Automatic Post Editing and Quality Estimation
... APE and QE training datasets consist of (SRC, M T, P E ) triples, where the post-edited reference is created by a human translator in the workflow described above. However, publicly available APE datasets are ... See full document
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Combining Quality Estimation and Automatic Post editing to Enhance Machine Translation output
... the neural decoder, which is already a stronger APE module on its ...the neural system ...the neural approach, which forces the APE system to perform a large number of changes, can be kept under ... See full document
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Proceedings of the AMTA 2018 Workshop on Translation Quality Estimation and Automatic Post Editing
... Bio: Marcin has been working in the Machine Translation team at Microsoft AI and Research -- Redmond as a Principal NLP Scientist since January 2018. Before joining Microsoft he was an Assistant Professor at the Adam ... See full document
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