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CUNI Submission to MT4All Shared Task

Publication at Faculty of Mathematics and Physics |
2022

Abstract

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