[PDF] Top 20 The ILSP/ARC submission to the WMT 2018 Parallel Corpus Filtering Shared Task
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The ILSP/ARC submission to the WMT 2018 Parallel Corpus Filtering Shared Task
... the submission of the Institute for Language and Speech Process- ing/Athena Research and Innovation Center (ILSP/ARC) for the WMT 2018 Parallel Cor- pus Filtering ... See full document
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The ILSP/ARC submission to the WMT 2016 Bilingual Document Alignment Shared Task
... We also examined manually all document pairs missed in our submission in order to gather useful insights that could help us improve our system. A first conclusion is that a major issue in evaluating bilingual ... See full document
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STACC, OOV Density and N gram Saturation: Vicomtech’s Participation in the WMT 2018 Shared Task on Parallel Corpus Filtering
... points below the top performing systems on aver- age. The n-gram saturation variant did not provide significant improvements and actually performed significantly worse in one scenario, while also consuming more ... See full document
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NRC Parallel Corpus Filtering System for WMT 2019
... WMT19 shared task on parallel corpus filter- ing was essentially the same as last year’s edi- tion (Koehn et ...noisy corpus crawled from the web using ParaCrawl (Koehn et ...of ... See full document
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The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task
... In this paper, we presented our rescoring system for the WMT 2019 Shared Task on Parallel Cor- pus Filtering. Our system is based on contrastive scoring models using features extracted ... See full document
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Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low Resource Conditions
... Specifically, we provided a very noisy 50- 60 million word (English token count) Nepali– English and Sinhala–English corpora crawled from the web using the Paracrawl processing pipeline (see Section 4.4 for details). We ... See full document
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Tilde’s Parallel Corpus Filtering Methods for WMT 2018
... describes parallel corpus filtering methods that allow reducing noise of noisy “parallel” corpora from a level where the cor- pora are not usable for neural machine trans- lation training ... See full document
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Learning Bilingual Sentence Embeddings via Autoencoding and Computing Similarities with a Multilayer Perceptron
... the WMT 2018 parallel corpus filtering task use large-scale neural MT models and lan- guage models as the features (Koehn et ...for parallel corpus min- ing and ... See full document
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JU Saarland Submission to the WMT2019 English–Gujarati Translation Shared Task
... in WMT 2019. We initially used monoses (Artetxe et al., 2018), which is based on unsupervised statistical phrase based machine translation, to translate the monolingual sentences from English to ... 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 ... See full document
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The RWTH Aachen University Filtering System for the WMT 2018 Parallel Corpus Filtering Task
... a filtering approach, we train a transformer model on the top 10M respec- tively top 100M subwords of the scored training ...al., 2018) and found their training behavior to be ... See full document
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Findings of the WMT 2018 Shared Task on Automatic Post Editing
... of parallel attention layers (4 and 8 ...the WMT‘17 Trans- lation task (Huck et ...the task, training is per- formed by taking advantage of both the artificial data provided by ... See full document
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SYSTRAN Participation to the WMT2018 Shared Task on Parallel Corpus Filtering
... our submission to the WMT18 shared task on parallel corpus ...identify parallel sen- tences using a flexible method that relies on deep neural ... See full document
5
Alibaba Submission to the WMT18 Parallel Corpus Filtering Task
... The parallel corpus is an essential resource for machine translation and multilingual natural lan- guage ...of parallel corpus is also very important in MT system training (Koehn and Knowles, ... See full document
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MAJE Submission to the WMT2018 Shared Task on Parallel Corpus Filtering
... our submission to the WMT18 shared task on parallel corpus ...the task as a QE problem, where we estimate how well two sentences correspond to each other to be part of a training ... See full document
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Coverage and Cynicism: The AFRL Submission to the WMT 2018 Parallel Corpus Filtering Task
... Optimizing the heuristic and empirical prefilter- ing and preprocessing steps given here could yield substantial benefit. We have doubtlessly removed some beneficial lines in the prefiltering, which ex- cluded up to 90% ... 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 ... See full document
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Findings of the WMT 2018 Shared Task on Parallel Corpus Filtering
... SMT For statistical machine translation, we used Moses (Koehn et al., 2007) with fairly ba- sic settings, such as Good-Turing smoothing of phrase table probabilities, maximum phrase length of 5, maximum sentence length ... See full document
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Webinterpret Submission to the WMT2019 Shared Task on Parallel Corpus Filtering
... German-English task last year, the organizers now pose the problem under more challenging low-resource conditions includ- ing Nepali and Sinhala ...the task addresses the challenge of data quality and not ... See full document
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Findings of the WMT 2018 Shared Task on Quality Estimation
... the task instances. In- terpretants provide context for the prediction task and are used during the derivation of the features measuring the closeness of the test sentences to the training data, the ... See full document
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