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2021 EMNLP EMNLP 2021

Improving Similar Language Translation With Transfer Learning

Abstract

AbstractWe investigate transfer learning based on pre-trained neural machine translation models to translate between (low-resource) similar languages. This work is part of our contribution to the WMT 2021 Similar Languages Translation Shared Task where we submitted models for different language pairs, including French-Bambara, Spanish-Catalan, and Spanish-Portuguese in both directions. Our models for Catalan-Spanish (82.79 BLEU)and Portuguese-Spanish (87.11 BLEU) rank top 1 in the official shared task evaluation, and we are the only team to submit models for the French-Bambara pairs.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — pre trained model
🐝 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, Security & Privacy, Speech & Audio

Authors

Ife Adebara , Muhammad Abdul-Mageed

Topics

Natural Language Processing > Applications > Machine Translation Machine Learning > Learning Paradigms > Transfer Learning Natural Language Processing > Generation > Machine Translation Deep Learning > Learning Types > Transfer Learning

Keywords

transfer learning neural machine translation low-resource language fine tuning low resource language similar language pre trained model
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