Architecture design of oral English evaluation system based on deep learning

The aim of this study is to develop a oral evaluation system based on deep learning to improve the accuracy and efficiency of oral evaluation. By studying the application of deep learning technology in speech recognition, feature extraction and model construction, a spoken language evaluation system including data preprocessing, feature extraction, model training and evaluation output is constructed. The experimental results show that the system has achieved a good evaluation effect on several public data sets, and can effectively evaluate the fluency, accuracy and completeness of spoken language.