@InProceedings{lo-EtAl:2018:C18-2,
  author    = {Lo, Yu-Chun  and  Chen, Jhih-Jie  and  Yang, Chingyu  and  Chang, Jason},
  title     = {Cool English: a Grammatical Error Correction System Based on Large Learner Corpora},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico},
  publisher = {Association for Computational Linguistics},
  pages     = {82--85},
  abstract  = {This paper presents a grammatical error correction (GEC) system that provides corrective feedback for essays. We apply the sequence-to-sequence model, which is frequently used in machine translation and text summarization, to this GEC task. The model is trained by EF-Cambridge Open Language Database (EFCAMDAT), a large learner corpus annotated with grammatical errors and corrections. Evaluation shows that our system achieves competitive performance on a number of publicly available testsets.},
  url       = {http://www.aclweb.org/anthology/C18-2018}
}