Chinese text automatic proofreading model based on Seq2Seq and Bi-LSTM

A new deep learning model based on Seq2Seq and Bi-LSTM is proposed for Chinese text automatic proofreading. Different from the traditional rule-based and probabilistic statistical methods, a Chinese text automatic proofreading model is implemented by adding Bi-LSTM unit and attention mechanism based on Seq2Seq infrastructure improvement. Comparative experiments of different models were carried out through the open data sets. Experimental results show that the new model can effectively deal with long-distance text errors and semantic errors. The addition of Bi-RNN and attention mechanism can improve the performance of Chinese text proofreading model.