A method for capturing English oral pronunciation errors based on speech recognition
by Wenna Dou
International Journal of Computing Science and Mathematics (IJCSM), Vol. 21, No. 1, 2025

Abstract: To improve the accuracy and timeliness of capturing pronunciation errors, the paper proposes a new method for capturing English oral pronunciation errors based on the speech recognition process. Using a voice production system to collect raw English spoken pronunciation signals and extract the features of the speech signals. Then, after determining the confidence level of the intonation points, hidden Markov model (HMM) classification algorithm is used to classify the intonation points and establish a spoken pronunciation comparison database containing standard state sequences. Finally, the degree component signal detection method is used to determine the spectral features of pronunciation errors. By comparing the spectral features with standard state sequences, incorrect English spoken pronunciation is captured. Experiment shows that the recognition accuracy of this method remains above 97%, and the maximum accuracy of capturing pronunciation errors can reach 98.74%. The capture time remains within 3s, indicating that this method has achieved the design expectations.

Online publication date: Tue, 06-May-2025

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