Research on Network Oral English Teaching System Based on Machine Learning

Abstract

With the development of computer science and technology and the advancement of language teaching and learning methods, computer-assisted language learning technology has made it possible to solve this problem. In the area of oral learning, some computer-assisted language learning systems at home and abroad mainly focus on the learning of words and grammar and only have one or two evaluation indicators as the basis of evaluation, which have certain functional defects and can only give an overall rating to learners’ pronunciation. To address these problems, this paper takes the English speech of Chinese college students as the research object and improves the traditional computerized English pronunciation quality evaluation method by considering multiplicative evaluation indexes, such as pitch, speed, rhythm, and intonation; i.e., pitch evaluation is based on frequency central feature parameters, speech speed evaluation based on speech duration, rhythm evaluation. The method of pitch, speed, rhythm, and intonation evaluation has been experimentally verified to be reliable. Furthermore, considering the weight of the above multiplicative evaluation indexes.