CUNI Submission to MT4All Shared Task

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457033" target="_blank" >RIV/00216208:11320/22:10457033 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

CUNI Submission to MT4All Shared Task

Original language description

This paper describes our submission to the MT4All Shared Task in unsupervised machine translation from English to Ukrainian, Kazakh and Georgian in the legal domain. In addition to the standard pipeline for unsupervised training (pretraining followed by denoising and back-translation), we used supervised training on a pseudo-parallel corpus retrieved from the provided monolingual corpora. Our system scored significantly higher than the baseline hybrid unsupervised MT system

Czech name

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Czech description

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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)

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)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the LREC 2022 Workshop of the 1st Annual Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages (SIGUL 2022)

ISBN

979-10-95546-91-7

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

78-82

Publisher name

European Language Resources Association (ELRA)

Place of publication

Paris, France

Event location

Marseille, France

Event date

Jun 24, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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