2021
EMNLP
EMNLP 2021
Adam Mickiewicz University’s English-Hausa Submissions to the WMT 2021 News Translation Task
Abstract
AbstractThis paper presents the Adam Mickiewicz University’s (AMU) submissions to the WMT 2021 News Translation Task. The submissions focus on the English↔Hausa translation directions, which is a low-resource translation scenario between distant languages. Our approach involves thorough data cleaning, transfer learning using a high-resource language pair, iterative training, and utilization of monolingual data via back-translation. We experiment with NMT and PB-SMT approaches alike, using the base Transformer architecture for all of the NMT models while utilizing PB-SMT systems as comparable baseline solutions.
🌉
Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
🐝
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
Topics
Natural Language Processing > Applications > Machine Translation
Machine Learning > Learning Paradigms > Transfer Learning
Natural Language Processing > Generation > Machine Translation
Deep Learning > Techniques > Knowledge Distillation
Deep Learning > Learning Types > Transfer Learning
Deep Learning > Learning Types > Machine Translation