Simulation research on interactive entertainment e-learning based on visual saliency testing in music multimedia teaching system

Abstract

In traditional music teaching method, students passively accept information and lack sufficient interaction and participation. Entertainment robots can provide students with a more interesting and engaging learning experience through means such as multimedia content, gamified elements and interactive design. The goal of this research is to develop a technology based on visual saliency testing to improve the performance of entertainment robots in music teaching systems, making them more intelligent and interactive. The research collected a large number of music multimedia teaching materials, and marked and analyzed them. The visual significance test method is used to determine the key points and important information in the teaching materials, and the computer vision technology is used to identify the areas of visual interest to students in real time. Through interaction with students, the system can adapt its output based on student feedback to ensure personalized exploration and teaching of students' points of interest. Finally, an interactive entertainment robot system is designed, which can perform intelligent feedback and interaction according to the significant information in music teaching materials. The results show that the entertainment robot system based on visual salience test shows higher intelligence and interactivity in music multimedia teaching, which greatly improves the teaching experience.