Linguistics and Languages

Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals

M. Popel, M. Tomkova, et al.

Discover CUBBITT, the groundbreaking deep-learning translation system that rivals human professionals! This research, conducted by Martin Popel and colleagues, showcases CUBBITT's remarkable ability to maintain adequacy and fluency in English-to-Czech news translation, outperforming previous systems and hinting at a new era of meaning-focused applications in translation.

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Index

Abstract

This study introduces CUBBITT, a deep-learning system that achieves news translation quality comparable to human professionals. In a blind evaluation, CUBBITT significantly outperformed professional-agency English-to-Czech news translation in preserving text meaning (adequacy). While human translation was rated as more fluent, CUBBITT showed substantially higher fluency than previous state-of-the-art systems. Many participants in a Turing test struggled to distinguish CUBBITT translations from human translations, suggesting deep learning's potential to replace humans in meaning-focused applications.

Publisher

Nature Communications

Published On

Oct 27, 2020

Authors

Martin Popel, Marketa Tomkova, Jakub Tomek, Lukasz Kaiser, Jakob Uszkoreit, Ondřej Bojar, Zdeněk Žabokrtský

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