English Speech Scoring System Based on Computer Neural Network

Abstract

 In English phonetics teaching, in order to improve students' English phonetics quality, a computer neural network based English phonetics scoring method is proposed. First, the frequency domain spectrogram is used as the data input to construct a convolutional neural network model at the word and phoneme levels to detect speech similarity. Then the original sound time domain waveform is used as the data input, which is converted into text through neural network to detect the text difference. Finally, we combine the two with the assigned weight to give a relatively objective comprehensive pronunciation score. The simulation results show that the method is accurate and practical, and can promote the standardization of students' English pronunciation.