Skip to content
conftrace_
2019 ACL ACL 2019

Multi-headed Architecture Based on BERT for Grammatical Errors Correction

AbstractIn this paper, we describe our approach to GEC using the BERT model for creation of encoded representation and some of our enhancements, namely, “Heads” 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.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing
🐣 Hot Topic Early Bird - error detection

More from ACL 2019

All ACL 2019 papers →