According to the distribution of Chinese single-character after word segmentation in Chinese text and the conception of "non-multi-character word error",we proposed a group of rules to find errors in texts,to construct the automatic error-detection model and to implement its algorithm by combining the scattered single-character Bigram models.

Based on automatic spelling check for English essays,the spelling errors in English compositions are classified into non-word and real-word errors.

This paper argues that real-word spelling errors are much more common than expected and the existing computer spelling checkers are not efficient enough to tackle all real-word errors.

Improved Word Error Rate evaluation algorithm for automatic speech recognition;

Based on the theory of error analysis,this thesis classifies the lexical errors in vocational college students English writing,including spelling errors,word-formation errors,misusage of synonymies and near-synonymies,misusage of prepositions and parts of speech.

Based on the theory of error analysis,this thesis classifies the lexical errors in Vocational College students’English writing,which can be divided into spelling errors,word-formation errors,misusage of synonymies and near-synonymies,misusage of prepositions and parts of speech.

Based on the essays written by 60 non-English-major students in our university,this paper examines and classifies the lexical errors made by the students.