CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks

2016/06/23 by Libovický, Jindřich, Helcl, Jindřich, Tlustý, Marek +2 · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.1606.07481

Abstract

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 utilize several recently published methods used for neural sequential learning in order to build systems for WMT 2016 shared tasks of Automatic Post-Editing and Multimodal Machine Translation.

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• Multimodal Machine Translation with Visual Scene Graph Pruning

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