Analysis and Improvement of the Effect of Listening Anxiety on College English Teaching Based on Neural Network

Listening is an important form of language input, especially for students. Language learning should be mainly based on auditory input, so listening plays a very important role in the process of language learning. Listening is one of the language skills most likely to cause anxiety in foreign language learners. In order to better analyze the impact of listening anxiety on the effect of college English teaching, we propose an analysis and improvement method based on a neural network model. The goal of this paper is to utilize a neural network model for analyzing the various factors that influence psychological anxiety of college students and to formulate targeted and directional countermeasures for the causes of this problem. We propose a neural network-based model for the English listening anxiety classification and recognition. Based on this method, we expect to effectively reduce the anxiety of college students in college English listening learning, so as to improve the quality of English listening teaching. Specifically, firstly, we design a questionnaire to collect data on students, such as anxiety level, reasons, difficulty of listening materials, classroom atmosphere, emotion. Secondly, we utilize the text material obtained from the questionnaire as training data for the model, and we design a text processing and transformation method. Thirdly, we design a feature extraction and anxiety classification method using a neural network model. Finally, through experiments with students in different classes, we have confirmed that the method proposed in this paper demonstrates excellent performance in classifying and recognizing English anxiety.