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2019 ACL ACL 2019

The AIP-Tohoku System at the BEA-2019 Shared Task

Abstract

AbstractWe introduce the AIP-Tohoku grammatical error correction (GEC) system for the BEA-2019 shared task in Track 1 (Restricted Track) and Track 2 (Unrestricted Track) using the same system architecture. Our system comprises two key components: error generation and sentence-level error detection. In particular, GEC with sentence-level grammatical error detection is a novel and versatile approach, and we experimentally demonstrate that it significantly improves the precision of the base model. Our system is ranked 9th in Track 1 and 2nd in Track 2.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — sentence-level error detection
🐣 Hot Topic Early Bird — error detection
🐝 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

Authors

Hiroki Asano , Masato Mita , Tomoya Mizumoto , Jun Suzuki

Topics

Machine Learning > Core Methods > Classification Natural Language Processing > Generation > Text Generation Natural Language Processing > Applications > Text Processing Deep Learning > Learning Types > Sequence Modeling

Keywords

grammatical error correction neural machine translation error detection text correction sentence-level classification sentence-level error detection
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