Machine Translation Error Recognition of English Online Education Resources Based on Informative Text

The quality of Machine translation of English online educational resources directly affects learners’ understanding and mastery of educational content. Therefore, accurate identification of errors in Machine translation can help improve the quality of educational resources and improve the learning effect. In order to improve the error recognition effect of machine translation of English online education resources and shorten the recognition time, this paper proposes an error recognition method of machine translation of English online education resources based on informative text. First, the learner corpus is constructed to extract the error characteristics of machine translation from English online education resources; Then, the multi sequence alignment optimization algorithm is used to extract attributes. Finally, the maximum matching score is considered to realize the recognition of error information text in machine translation of online language education resources. The experimental results show that the English translation error recognition time of the proposed method is 16.0 s, and the recognition accuracy can reach 98.5%. The above results indicate that the proposed method can effectively improve the efficiency of English translation error recognition.