2022
EMNLP
EMNLP 2022
Tackling Low-Resourced Sign Language Translation: UPC at WMT-SLT 22
Abstract
AbstractThis paper describes the system developed at the Universitat Politècnica de Catalunya for the Workshop on Machine Translation 2022 Sign Language Translation Task, in particular, for the sign-to-text direction. We use a Transformer model implemented with the Fairseq modeling toolkit. We have experimented with the vocabulary size, data augmentation techniques and pretraining the model with the PHOENIX-14T dataset. Our system obtains 0.50 BLEU score for the test set, improving the organizers’ baseline by 0.38 BLEU. We remark the poor results for both the baseline and our system, and thus, the unreliability of our findings.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— fairseq toolkit
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Hot Topic Early Bird
— sign language translation
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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, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Application Areas > Data Augmentation
Natural Language Processing > Applications > Machine Translation
Machine Learning > Learning Paradigms > Transfer Learning
Natural Language Processing > Generation > Machine Translation
Deep Learning > Models > Transformers
Deep Learning > Learning Types > Transfer Learning
Deep Learning > Learning Types > Data Augmentation