Chinese Spelling Correction (CSC) is a task to detect and correct spelling mistakes in texts. In fact, most of Chinese input is based on pinyin input method, so the study of spelling errors in this process is more practical and valuable. However, there is still no research dedicated to this essential scenario. In this paper, we first present a Chinese Spelling Correction Dataset for errors generated by pinyin IME (CSCD-IME), including 40,000 annotated sentences from real posts of official media on Sina Weibo. Furthermore, we propose a novel method to automatically construct large-scale and high-quality pseudo data by simulating the input through pinyin IME. A series of analyses and experiments on CSCD-IME show that spelling errors produced by pinyin IME hold a particular distribution at pinyin level and semantic level and are challenging enough. Meanwhile, our proposed pseudo-data construction method can better fit this error distribution and improve the performance of CSC systems. Finally, we also provide a useful guide to using pseudo data, including the data scale, the data source, and the training strategy

该论文介绍了一个由真实社交媒体数据构成的对拼音输入法产生的中文拼写错误进行检测和纠正的数据集（CSCD-IME），并提出了利用拼音输入法自动生成大规模高质量的伪数据的方法，实验结果表明，我们提出的伪数据构建方法能够更好地适应这种错误分布并提高CSC系统的性能。

CSCD-IME：拼音输入法生成的拼写错误修正