Machine Translation of Covid-19 Information Resources via Multilingual Transfer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10440554" target="_blank" >RIV/00216208:11320/21:10440554 - isvavai.cz</a>
Result on the web
<a href="https://ics.upjs.sk/~antoni/ceur-ws.org/Vol-0000/paper26.pdf" target="_blank" >https://ics.upjs.sk/~antoni/ceur-ws.org/Vol-0000/paper26.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Machine Translation of Covid-19 Information Resources via Multilingual Transfer
Original language description
The Covid-19 pandemic has created a global demand for accurate and up-to-date information which often originates in English and needs to be translated. To train a machine translation system for such a narrow topic, we leverage in-domain training data in other languages both from related and unrelated language families. We experiment with different transfer learning schedules and observe that transferring via more than one auxiliary language brings the most improvement. We compare the performance with joint multilingual training and report superior results of the transfer learning approach.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
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
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů