2022
EMNLP
EMNLP 2022
Findings of the WMT 2022 Shared Task on Automatic Post-Editing
Abstract
AbstractWe present the results from the 8th round of the WMT shared task on MT Automatic PostEditing, which consists in automatically correcting the output of a “black-box” machine translation system by learning from human corrections. This year, the task focused on a new language pair (English→Marathi) and on data coming from multiple domains (healthcare, tourism, and general/news). Although according to several indicators this round was of medium-high difficulty compared to the past,the best submission from the three participating teams managed to significantly improve (with an error reduction of 3.49 TER points) the original translations produced by a generic neural MT system.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Keyword Pioneer
— translation error reduction
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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