CUNI Systems for the Unsupervised and Very Low Resource Translation Task in WMT20
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424466" target="_blank" >RIV/00216208:11320/20:10424466 - 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 Systems for the Unsupervised and Very Low Resource Translation Task in WMT20
Original language description
This paper presents a description of CUNI systems submitted to the WMT20 task on unsupervised and very low-resource supervised machine translation between German and Upper Sorbian. We experimented with training on synthetic data and pre-training on a related language pair. In the fully unsupervised scenario, we achieved 25.5 and 23.7 BLEU translating from and into Upper Sorbian, respectively. Our low-resource systems relied on transfer learning from German-Czech parallel data and achieved 57.4 BLEU and 56.1 BLEU, which is an improvement of 10 BLEU points over the baseline trained only on the available small German-Upper Sorbian parallel corpus.
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Fifth Conference on Machine Translation - Proceedings of the Conference
ISBN
978-1-948087-81-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1123-1128
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Online
Event date
Nov 19, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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