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.

The analysis of the wrong word choice by college English learners suggests that the major sources in word choice are located in five aspects.