An Intelligent Language Tutoring System for Handling Errors Caused by Transfer
ITS '92 Proceedings of the Second International Conference on Intelligent Tutoring Systems
Recognizing syntactic errors in the writing of second language learners
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Correcting ESL errors using phrasal SMT techniques
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The Unreasonable Effectiveness of Data
IEEE Intelligent Systems
The ups and downs of preposition error detection in ESL writing
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
NRC's PORTAGE system for WMT 2007
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Detection of grammatical errors involving prepositions
SigSem '07 Proceedings of the Fourth ACL-SIGSEM Workshop on Prepositions
Exploring grammatical error correction with not-so-crummy machine translation
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
Evidence in automatic error correction improves learners' english skill
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Bucking the trend: improved evaluation and annotation practices for ESL error detection systems
Language Resources and Evaluation
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In this paper, we investigate a novel approach to correcting grammatical and lexical errors in texts written by second language authors. Contrary to previous approaches which tend to use unilingual models of the user's second language (L2), this new approach uses a simple roundtrip Machine Translation method which leverages information about both the author's first (L1) and second languages. We compare the repair rate of this roundtrip translation approach to that of an existing approach based on a unilingual L2 model with shallow syntactic pruning, on a series of preposition choice errors. We find no statistically significant difference between the two approaches, but find that a hybrid combination of both does perform significantly better than either one in isolation. Finally, we illustrate how the translation approach has the potential of repairing very complex errors which would be hard to treat without leveraging knowledge of the author's L1.