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2019 ACL ACL 2019

CUNI Submission for Low-Resource Languages in WMT News 2019

Abstract

AbstractThis paper describes the CUNI submission to the WMT 2019 News Translation Shared Task for the low-resource languages: Gujarati-English and Kazakh-English. We participated in both language pairs in both translation directions. Our system combines transfer learning from a different high-resource language pair followed by training on backtranslated monolingual data. Thanks to the simultaneous training in both directions, we can iterate the backtranslation process. We are using the Transformer model in a constrained submission.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Natural Language Processing
🐣 Hot Topic Early Bird — low-resource language
🐝 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, Robotics, Speech & Audio

Authors

Tom Kocmi , Ondřej Bojar

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Learning Types > Zero-Shot Learning Natural Language Processing > Applications > Machine Translation Machine Learning > Learning Types > Transfer Learning Natural Language Processing > Generation > Machine Translation

Keywords

transfer learning neural machine translation low-resource language low-resource translation unsupervised machine translation
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