Innovation of college pop music teaching in traditional music culture based on robot cognitive-emotional interaction model

Abstract

Emotional computing and artificial psychology is a new research direction that has received increasing attention in the field of harmonious human-computer interaction and artificial intelligence and is also a new intersection of mathematics, information science, intelligence science, neuroscience, physiology, psychological science and other multidisciplinary intersection. The current problems and drawbacks in the teaching of popular music in colleges and universities, and the search for methods and measures to reform and innovate popular music education in colleges and universities are the difficulties of current music teaching work. In this paper, we try to apply a robot cognitive-emotional interaction model to college pop music teaching, and establish an emotional interaction model based on reinforcement learning with the help of cognitive-emotional computing of human-computer interaction, to be able to integrate emotional interaction in pop music teaching and to make an accurate emotional analysis of students' singing effect. Different from traditional music teaching methods, the robot-based cognitive-emotional interaction model established in this paper can establish an innovative teaching model for college pop music teaching and optimize the teaching effect.