CUNI NMT System for WAT 2018 Translation Tasks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10390164" target="_blank" >RIV/00216208:11320/18:10390164 - isvavai.cz</a>
Result on the web
<a href="http://lotus.kuee.kyoto-u.ac.jp/WAT/WAT2018/WAT2018-proceedings-20181204.zip" target="_blank" >http://lotus.kuee.kyoto-u.ac.jp/WAT/WAT2018/WAT2018-proceedings-20181204.zip</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
CUNI NMT System for WAT 2018 Translation Tasks
Original language description
This paper describes the CUNI submission to WAT 2018 for the English-Hindi translation task using a transfer learning techniques which has proven effective under low resource conditions. We have used the Transformer model and utilized an English-Czech parallel corpus as additional data source. Our simple transfer learning approach first trains a "parent" model for a high-resource language pair (English-Czech) and then continues the training on the low-resource (English-Hindi) pair by replacing the training corpus. This setup improves the performance compared with the baseline and in combination with back-translation of Hindi monolingual data, it allowed us to win the English-Hindi task. The automatic scoring by BLEU did not correlate well with human judgments.
Czech name
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Czech description
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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)

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)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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