2019
ACL
ACL 2019
Multi-headed Architecture Based on BERT for Grammatical Errors Correction
Abstract
AbstractIn this paper, we describe our approach to GEC using the BERT model for creation of encoded representation and some of our enhancements, namely, βHeadsβ are fully-connected networks which are used for finding the errors and later receive recommendation from the networks on dealing with a highlighted part of the sentence only. Among the main advantages of our solution is increasing the system productivity and lowering the time of processing while keeping the high accuracy of GEC results.
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Interdisciplinary Bridge
β Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
β multi-headed architecture
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Hot Topic Early Bird
β error detection
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Cross-Pollinator
β 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