Abstract
Aiming at the low confidence of traditional spoken English automatic evaluation methods, this study designs an automatic evaluation method of spoken English based on multimodal discourse analysis theory. This evaluation method uses sound sensors to collect spoken English pronunciation signals, decomposes the spoken English speech signals by multilayer wavelet feature scale transform, and carries out adaptive filter detection and spectrum analysis on spoken English speech signals according to the results of feature decomposition. Based on multimodal discourse analysis theory, this evaluation method can extract the automatic evaluation features of spoken English and automatically recognize the speech quality according to the results. The experimental results show that, compared with the control group, the designed evaluation method has obvious advantages in confidence evaluation and can solve the problem of low confidence of traditional oral automatic evaluation methods.
Highlights
Modern signal processing and automatic pattern recognition technology are used to distinguish the quality of oral English pronunciation
E research on the automatic evaluation method of oral English pronunciation quality is based on speech signal detection and feature extraction, using intelligent signal processing technology, combined with time-frequency feature analysis and spectral analysis of oral English pronunciation signals, so as to improve the automation and intelligence level of oral English pronunciation quality evaluation. e research on the optimization design method of the automatic evaluation system of oral English pronunciation quality has a good application value in the design of oral English teaching. e related research on the automatic evaluation system method of oral English pronunciation quality has attracted great attention
In the automatic evaluation system of oral English pronunciation quality, the oral English pronunciation signal is affected by the disturbance and distortion of oral pronunciation channel, which leads to the poor accuracy of oral English pronunciation quality evaluation. e change of oral features produces speech attenuation and distortion, which leads to the decline of the accurate detection performance of the automatic evaluation system of oral English pronunciation quality
Summary
Modern signal processing and automatic pattern recognition technology are used to distinguish the quality of oral English pronunciation. Combined with signal detection and speech signal feature extraction methods, oral English automatic evaluation is carried out to improve the objectivity and accuracy of oral English pronunciation quality evaluation. E research on the automatic evaluation method of oral English pronunciation quality is based on speech signal detection and feature extraction, using intelligent signal processing technology, combined with time-frequency feature analysis and spectral analysis of oral English pronunciation signals, so as to improve the automation and intelligence level of oral English pronunciation quality evaluation. Combined with artificial intelligence control and feature extraction, the performance of oral English pronunciation quality automatic evaluation system is improved, and some research results are obtained. E time-frequency feature decomposition method is used for speech recognition of the automatic evaluation system of oral English pronunciation quality. We can capture the multimodal symbols of oral English and extract the automatic evaluation features of oral English, so as to explore the multimodal symbols in college oral English teaching at the microlevel, so as to enlarge the details of oral English teaching, promote the long-term development of college oral English teaching, strive to solve the problems existing in the traditional oral English automatic evaluation methods, and fundamentally improve the confidence of oral English automatic evaluation
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