No matter that learning Chinese as a first or second language, a quite important issue, misspelled words, needs to be addressed. Many studies proposed that there was a suggestion of correcting misspelled words for students who are still schooling as well as a suggestion of teaching and learning strategies of Chinese characters for teachers. Although in schooling, it does to prevent students who do lots of precautions and corrections from generating misspelled words; students sometimes are unconscious of their misspelled words while writing. As a result, in addition to emphasize the recognition of misspelled words in teaching, mentioning how to prevent from generating misspelled words during the process of using words becomes a critical issue. Nevertheless, it is not an easy matter to find misspelled words automatically and correctly within documents by using formula. Currently, there are researchers conducting research on graphemic misspelled words detection and applying it to different fields. But the accuracy is still far from the real demand. If it can analyze the model, probability and context of misspelled words in detail, it could be detecting the misspelled words more quickly and precisely as well as correcting those words effectively. We had been already accumulated quite research experiences on graphemic misspelled words. This project will combine with resources provided by the mainline project to process the problem of graphemic misspelled words. If it can achieve a breakthrough, it will not only offer a quite effective auxiliary tool for teaching Chinese misspelled words, but assist in establishing a learning tool of Chinese character errors corpus more quickly.