篇名 | Chinese Spelling Check based on Neural Machine Translation |
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卷期 | 25:1 |
作者 | Jhih-Jie Chen 、 Hai-Lun Tu 、 Ching-Yu Yang 、 Chiao-Wen Li 、 Jason S. Chang |
頁次 | 001-028 |
關鍵字 | Chinese Spelling Check 、 Artificial Error Generation 、 Neural Machine Translation 、 Edit Log 、 THCI Core |
出刊日期 | 202006 |
We present a method for Chinese spelling check that automatically learns to correct a sentence with potential spelling errors. In our approach, a character-based neural machine translation (NMT) model is trained to translate the potentially misspelled sentence into correct one, using right-and-wrong sentence pairs from newspaper edit logs and artificially generated data. The method involves extracting sentences contain edit of spelling correction from edit logs, using commonly confused right-and-wrong word pairs to generate artificial right-and-wrong sentence pairs in order to expand our training data , and training the NMT model. The evaluation on the United Daily News (UDN) Edit Logs and SIGHAN-7 Shared Task shows that adding artificial error data can significantly improve the performance of Chinese spelling check system.