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Using Contextual Speller Techniques and Language Modeling for ESL Error Correction. Proceedings of IJCNLP, Hyderabad, India.

Michael Gamon, Jianfeng Gao, Chris Brockett, Alexander Klementiev, William Dolan, Dmitriy Belenko, and Lucy Vanderwende

Abstract

We present a modular system for detection and correction of errors made by non-native (English as a Second Language = ESL) writers. We focus on two error types: the incorrect use of determiners and the choice of prepositions. We use a decision-tree approach inspired by contextual spelling systems for detection and correction suggestions, and a large language model trained on the Gigaword corpus to provide additional information to filter out spurious suggestions. We show how this system performs on a corpus of non-native English text and discuss strategies for future enhancements.

Details

Publication typeInproceedings
URLhttp://www.afnlp.org/
PublisherAsia Federation of Natural Language Processing
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