Design and Application of English Pronunciation Correction Algorithm Based on SVM and LDA

The standardization of English pronunciation is crucial for communication in English, and correct and standardized English pronunciation can greatly improve communication efficiency among English users. Therefore, it is worth studying the correction of pronunciation for English learners. This article suggests that two techniques, SVM (Support Vector Machine) and LDA (Latent Dirichlet Allocation), can be used to extract speech text features and construct an English pronunciation correction model. Finally a comparative experiment is conducted between the method proposed in this paper and the conventional model. In terms of the average accuracy of error correction, the error correction model constructed based on the method proposed in this paper is 95.62%, while the conventional model is 92.20%. The difference between the two is quite significant, proving that the method proposed in this paper can indeed assist in the design of English pronunciation error correction models.