CUNI System for the WMT19 Robustness Task
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10405569" target="_blank" >RIV/00216208:11320/19:10405569 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
CUNI System for the WMT19 Robustness Task
Original language description
We present our submission to the WMT19 Robustness Task. Our baseline system is the CUNI Transformer system trained for the WMT18 shared task on News Translation. Quantitative results show that the CUNI Transformer system is already far more robust to noisy input than the LSTM-based baseline provided by the task organizers. We further improved the performance of our model by fine-tuning on the in-domain noisy data.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GX19-26934X" target="_blank" >GX19-26934X: Neural Representations in Multi-modal and Multi-lingual Modeling</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Fourth Conference on Machine Translation - Proceedings of the Conference
ISBN
978-1-950737-27-7
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
738-742
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Firenze, Italy
Event date
Aug 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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