2020
ACL
ACL 2020
Grapheme-to-Phoneme Conversion with a Multilingual Transformer Model
Abstract
AbstractIn this paper, we describe our three submissions to the SIGMORPHON 2020 shared task 1 on grapheme-to-phoneme conversion for 15 languages. We experimented with a single multilingual transformer model. We observed that the multilingual model achieves results on par with our separately trained monolingual models and is even able to avoid a few of the errors made by the monolingual models.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Speech & Audio
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Keyword Pioneer
— monolingual model
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Hot Topic Early Bird
— multilingual transformer
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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, Security & Privacy, Speech & Audio