CUNI System for WMT17 Automatic Post-Editing Task
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Automatic Post-EditingMachine TranslationSimilar Papers 제목 키워드 기반
CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks
Neural sequence to sequence learning recently became a very promising paradigm in machine translation, achieving competitive results with statistical phrase-based systems. In this system description paper, we attempt to …
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We describe our two NMT systems submitted to the WMT2021 shared task in English-Czech news translation: CUNI-DocTransformer (document-level CUBBITT) and CUNI-Marian-Baselines. We improve the former with a better sentence…
NMTSegmentationSentenceSentence segmentation+1Adapting Neural Machine Translation for Automatic Post-Editing
Automatic post-editing (APE) models are usedto correct machine translation (MT) system outputs by learning from human post-editing patterns. We present the system used in our submission to the WMT’21 Automatic Post-Editi…
Automatic Post-EditingMachine TranslationTranslationLIG-CRIStAL System for the WMT17 Automatic Post-Editing Task
This paper presents the LIG-CRIStAL submission to the shared Automatic Post- Editing task of WMT 2017. We propose two neural post-editing models: a monosource model with a task-specific attention mechanism, which perform…
Automatic Post-Editingde-enSentenceInstance Selection for Online Automatic Post-Editing in a multi-domain scenario
In recent years, several end-to-end online translation systems have been proposed to successfully incorporate human post-editing feedback in the translation workflow. The performance of these systems in a multi-domain tr…
Automatic Post-EditingDecoderInformation RetrievalMachine Translation+2