2019
ACL
ACL 2019
Tilde’s Machine Translation Systems for WMT 2019
Abstract
AbstractThe paper describes the development process of Tilde’s NMT systems for the WMT 2019 shared task on news translation. We trained systems for the English-Lithuanian and Lithuanian-English translation directions in constrained and unconstrained tracks. We build upon the best methods of the previous year’s competition and combine them with recent advancements in the field. We also present a new method to ensure source domain adherence in back-translated data. Our systems achieved a shared first place in human evaluation.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Keyword Pioneer
— domain adherence
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Hot Topic Early Bird
— low-resource language
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio
Authors
Topics
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Applications > Machine Translation
Natural Language Processing > Generation > Machine Translation
Deep Learning > Models > Neural Networks
Deep Learning > Learning Types > Transfer Learning
Deep Learning > Learning Types > Machine Translation