TY - JOUR AU - Chollampatt, Shamil AU - Ng, Hwee Tou PY - 2018/04/26 Y2 - 2024/03/29 TI - A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 32 IS - 1 SE - Main Track: NLP and Text Mining DO - 10.1609/aaai.v32i1.12069 UR - https://ojs.aaai.org/index.php/AAAI/article/view/12069 SP - AB - <p> We improve automatic correction of grammatical, orthographic, and collocation errors in text using a multilayer convolutional encoder-decoder neural network. The network is initialized with embeddings that make use of character N-gram information to better suit this task. When evaluated on common benchmark test data sets (CoNLL-2014 and JFLEG), our model substantially outperforms all prior neural approaches on this task as well as strong statistical machine translation-based systems with neural and task-specific features trained on the same data. Our analysis shows the superiority of convolutional neural networks over recurrent neural networks such as long short-term memory (LSTM) networks in capturing the local context via attention, and thereby improving the coverage in correcting grammatical errors. By ensembling multiple models, and incorporating an N-gram language model and edit features via rescoring, our novel method becomes the first neural approach to outperform the current state-of-the-art statistical machine translation-based approach, both in terms of grammaticality and fluency. </p> ER -