[PDF] Top 20 PROMT Systems for WMT 2018 Shared Translation Task
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PROMT Systems for WMT 2018 Shared Translation Task
... factored translation yet, so we couldn’t teach the system to output the case feature for our ...the translation with names processing to be our final submission as we decided that a system which is a little ... See full document
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Findings of the WMT 2018 Shared Task on Parallel Corpus Filtering
... Learning weights for scoring functions. Given a large number of scoring functions, simply av- eraging their resulting scores may be inadequate. Learning weights to optimize machine translation system quality is ... See full document
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The JHU Machine Translation Systems for WMT 2018
... Rico Sennrich, Alexandra Birch, Anna Currey, Ulrich Germann, Barry Haddow, Kenneth Heafield, An- tonio Valerio Miceli Barone, and Philip Williams. 2017. The university of edinburgh’s neural MT systems for wmt17. ... See full document
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Tilde’s Machine Translation Systems for WMT 2017
... the top-scoring results for multiple language pairs in the WMT 2016 shared task in news translation. It is an encoder-decoder model with attention. The main distinction of our model is the use ... See full document
8
The University of Illinois submission to the WMT 2015 Shared Translation Task
... Table 1 shows the output of our systems on the testing data from WMT 2015. We report the scores that were obtained from Moses eval- uation scripts using multi-BLEU; the numbers in the shared ... See full document
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Findings of the WMT 2018 Shared Task on Automatic Post Editing
... “TER (pe+ref)”) and 3.22 BLEU points (from 62.99 to 66.21). Interestingly, except for one sys- tem, all the results show larger variations when computed with “BLEU (pe+ref)”, with a differ- ence of 0.97 TER points (from ... See full document
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Prompsit’s submission to WMT 2018 Parallel Corpus Filtering shared task
... The WMT 2018 parallel corpus filtering shared task partially shares its objectives with the First Automatic Translation Memory Cleaning Shared Task (Barbu et ...classify ... See full document
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Multi encoder Transformer Network for Automatic Post Editing
... the WMT 2018 shared task on Automatic Post-Editing ...machine translation output, the source and the post- edited translation in APE ...PBSMT task and -0.13 TER and +0.40 ... See full document
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Edinburgh’s Submission to all Tracks of the WMT 2009 Shared Task with Reordering and Speed Improvements to Moses
... The shared task is also an opportunity to incor- porate novel contributions and test them against the best machine translation systems for these lan- guage ... See full document
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Findings of the WMT 2017 Biomedical Translation Shared Task
... and Kneser-Ney discounting were used to estimate 5-gram language models (LM). For word align- ment, GIZA++ with the default grow-diag-final- and alignment symmetrization method was used. Tuning of the SMT systems ... See full document
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Tilde’s Machine Translation Systems for WMT 2018
... machine translation (NMT) is a rapidly changing research ...NMT systems first showed to achieve significantly bet- ter results than statistical machine translation (SMT) systems (Bojar et ... See full document
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CUNI Systems for the Unsupervised News Translation Task in WMT 2019
... Our translation systems submitted to WMT19 were created in several steps. Following the strat- egy of Artetxe et al. (2018b), we first train mono- lingual phrase embeddings and map them to the cross-lingual ... See full document
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Noisy Parallel Corpus Filtering through Projected Word Embeddings
... the WMT 2019 par- allel corpus filtering shared task is to select the 5 million words of parallel sentences producing the highest-quality machine translation system, given a set of ... See full document
5
LMU Munich’s Neural Machine Translation Systems at WMT 2018
... neural translation model for ...the translation quality of medical texts im- proves compared to our previous year’s WMT17 biomedical task submission (Huck et ...other translation direc- tion, ... See full document
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Huawei’s NMT Systems for the WMT 2019 Biomedical Translation Task
... • In order to alleviate the out-of-vocabulary problem, subword segmentation (Sennrich et al., 2016) is used as well. Instead of training an individual segmentation model for each language independently, we directly use ... See full document
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The ILSP/ARC submission to the WMT 2018 Parallel Corpus Filtering Shared Task
... By comparing the results of the two alternative ranking schemes, we conclude that their perfor- mances are similar for the 100M corpora. This is explained by the fact that their intersection is ex- tremely high: 5.2M ... See full document
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NTT’s Neural Machine Translation Systems for WMT 2018
... This paper describes NTT’s submission to the WMT 2018 news translation task (Bojar et al., 2018). This year, we participated in English-to- German (En-De) and German-to-English (De-En) ... See full document
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UFRGS Participation on the WMT Biomedical Translation Shared Task
... NMT systems can improve translation performance, espe- cially when using a many-to-one scheme ...that systems trained us- ing (ES+PT)→EN, for instance, may pro- duce better results due to the ... See full document
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Findings of the WMT 2018 Biomedical Translation Shared Task: Evaluation on Medline test sets
... the systems performed well on these isolated segments (ex- cept for one occurrence of ”Materials and Meth- ods” translated by ”Mat´eriaux et Proc´ed´es” in- stead of the usual ”Mat´eriel et M´ethodes”), which may ... See full document
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PROMT Translation Systems for WMT 2016 Translation Tasks
... Data The 2016 system is based on the exist- ing PROMT 2015 system. The 2015 system uses OPUS data (except IT documentation cor- pora and Subtitles) and company private paral- lel data (which consists mostly of ... See full document
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