This paper describes our use of phrasebased statistical machine translation (PB-SMT) for the automatic correction of errors in learner text in our submission to the CoNLL 2013 Shared Task on Grammatical Error Correction. Since the limited training data provided for the task was insufficient for training an effective SMT system, we also explored alternative ways of generating pairs of incorrect and correct sentences automatically from other existing learner corpora. Our approach does not yield particularly high performance but reveals many problems that require careful attention when building SMT systems for error correction.
REF added other learner corpora to the provided training data.
Constrained Grammatical Error Correction using Statistical Machine Translation
CoNLL
Computer Science