Application of Artificial Intelligence Technology to Assist Music Teaching in University Classrooms

There are problems in college music teaching, such as insufficient personalized teaching and difficulty in improving students' music literacy. This study adopts the MLP-assisted music teaching method to promote the comprehensive development of students' music literacy. This paper uses speech recognition technology and natural language processing capabilities to accurately analyze students' music learning needs. By collecting students' music works, practice records and online interaction data, students' music level, interest preferences and learning difficulties are identified. Secondly, based on the multi-layer perceptron (MLP), a personalized music teaching model is constructed. According to the students' own learning characteristics and needs, the model recommends suitable music tracks, practice methods and teaching resources. This paper introduces virtual reality (VR) and augmented reality (AR) technology to stimulate stud6 ents' learning interest and improve their music perception and performance skills by simulating real music scenes and performance experiences. Finally, this paper establishes a music teaching feedback mechanism to collect and analyze students' satisfaction and opinions on auxiliary teaching. After the introduction of MLP, the attendance rate of students in class increased, the skill test scores increased from 65-83 points to 83-99 points, and the number of classroom interactions increased from an average of 5.3 times to 11.7 times. The above experimental data show that MLP effectively enhances students' learning enthusiasm and skill level, and provides new technical support and innovative ideas for music teaching.