2023
ACL
ACL 2023
Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models
Abstract
AbstractThis paper describes CIC NLP’s submission to the AmericasNLP 2023 Shared Task on machine translation systems for indigenous languages of the Americas. We present the system descriptions for three methods. We used two multilingual models, namely M2M-100 and mBART50, and one bilingual (one-to-one) — Helsinki NLP Spanish-English translation model, and experimented with different transfer learning setups. We experimented with 11 languages from America and report the setups we used as well as the results we achieved. Overall, the mBART setup was able to improve upon the baseline for three out of the eleven languages.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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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
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Hot Topic Early Bird
— indigenous language
Authors
Topics
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Generation > Language Modeling
Natural Language Processing > Applications > Machine Translation
Natural Language Processing > Resources & Methods > Multilingual NLP
Machine Learning > Learning Types > Transfer Learning
Natural Language Processing > Generation > Machine Translation
Deep Learning > Models > Transformers
Deep Learning > Learning Types > Multi-Modal Learning