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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10335490" target="_blank" >RIV/00216208:11320/16:10335490 - isvavai.cz</a>
Result on the web
<a href="http://www.statmt.org/wmt16/pdf/W16-2361.pdf" target="_blank" >http://www.statmt.org/wmt16/pdf/W16-2361.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks
Original language description
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.
Czech name
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Czech description
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Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the First Conference on Machine Translation (WMT). Volume 2: Shared Task Papers
ISBN
978-1-945626-10-4
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
646-654
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Berlin, Germany
Event date
Aug 11, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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