System Combination for Grammatical Error Correction

Different approaches to high-quality grammatical error correction have been proposed recently, many of which have their own strengths and weaknesses. Most of these approaches are based on classi-fication or statistical machine translation (SMT). In this paper, we propose to com-bine the output from a classification-based system and an SMT-based system to improve the correction quality. We adopt the system combination technique of Heafield and Lavie (2010). We achieve an F0.5 score of 39.39 % on the test set of the CoNLL-2014 shared task, outperforming the best system in the shared task.