2019
ACL
ACL 2019
Baidu Neural Machine Translation Systems for WMT19
Abstract
AbstractIn this paper we introduce the systems Baidu submitted for the WMT19 shared task on Chinese<->English news translation. Our systems are based on the Transformer architecture with some effective improvements. Data selection, back translation, data augmentation, knowledge distillation, domain adaptation, model ensemble and re-ranking are employed and proven effective in our experiments. Our Chinese->English system achieved the highest case-sensitive BLEU score among all constrained submissions, and our English->Chinese system ranked the second in all submissions.
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Hot Topic Early Bird
— knowledge distillation
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
Authors
Topics
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Applications > Machine Translation
Machine Learning > Learning Types > Multi-Task Learning
Natural Language Processing > Generation > Machine Translation
Deep Learning > Techniques > Knowledge Distillation
Deep Learning > Learning Types > Knowledge Distillation