CUNI System for the WMT17 Multimodal Translation Task
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Image CaptioningMachine TranslationTranslationSimilar 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 …
Automatic Post-EditingMachine TranslationMultimodal Machine TranslationTranslationCUNI System for the WMT17 Multimodal Translation Task
In this paper, we describe our submissions to the WMT17 Multimodal Translation Task. For Task 1 (multimodal translation), our best scoring system is a purely textual neural translation of the source image caption to the …
Image CaptioningTask 2TranslationCUNI Systems in WMT21: Revisiting Backtranslation Techniques for English-Czech NMT
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…
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We present our submission to the WMT19 Robustness Task. Our baseline system is the Charles University (CUNI) Transformer system trained for the WMT18 shared task on News Translation. Quantitative results show that the CU…
TranslationCUNI System for the WMT18 Multimodal Translation Task
We present our submission to the WMT18 Multimodal Translation Task. The main feature of our submission is applying a self-attentive network instead of a recurrent neural network. We evaluate two methods of incorporating …
Translation