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

Add code
Jun 23, 2016
Jindřich Libovický, Jindřich Helcl, Marek Tlustý, Pavel Pecina, Ondřej Bojar
Figure 1 for CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks
Figure 2 for CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks
Figure 3 for CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks
Figure 4 for CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks

Share this with someone who'll enjoy it:

Twitter IconFacebook IconLinkedin IconWhatsapp IconMessenger Icon

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.

* Accepted to the First Conference of Machine Translation (WMT16)  
View paper onarxiv icon

Share this with someone who'll enjoy it:

Twitter IconFacebook IconLinkedin IconWhatsapp IconMessenger Icon