2020
EMNLP
EMNLP 2020
Findings of the 2020 Conference on Machine Translation (WMT20)
Abstract
AbstractThis paper presents the results of the news translation task and the similar language translation task, both organised alongside the Conference on Machine Translation (WMT) 2020. In the news task, participants were asked to build machine translation systems for any of 11 language pairs, to be evaluated on test sets consisting mainly of news stories. The task was also opened up to additional test suites to probe specific aspects of translation. In the similar language translation task, participants built machine translation systems for translating between closely related pairs of languages.
👥
Mega-Team
— 21 authors
🌉
Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Hot Topic Early Bird
— translation evaluation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio
Authors
Loic Barrault
,
Magdalena Biesialska
,
Ondřej Bojar
,
Marta R. Costa-jussà
,
Christian Federmann
,
Yvette Graham
,
Roman Grundkiewicz
,
Barry Haddow
,
Matthias Huck
,
Eric Joanis
,
Tom Kocmi
,
Philipp Koehn
,
Chi-kiu Lo
,
Nikola Ljubešić
,
Christof Monz
,
Makoto Morishita
,
Masaaki Nagata
,
Toshiaki Nakazawa
,
Santanu Pal
,
Matt Post
,
Marcos Zampieri