In this paper, immersive multimedia information technology is utilized to perform frame-splitting and window-adding operations on vocal signals in college vocal music teaching to facilitate the extraction of vocal signal features. According to the Principal Component Analysis feature space projection and Relief feature selection, the vocal emotion regression model combining multimedia information technology is constructed, and the structure of the vocal emotion regression model and its teaching application are explored in the vocal emotion regression model. Determine the research object and method, according to the research program on the integration of multimedia information technology of vocal music teaching research design and implementation, and the use of statistical analysis of multimedia information technology-based vocal music teaching empirical analysis. The results show that the subjects had the best emotional experience with an emotional immersion degree of 5.651 when the music of the calm category and the visual music motion picture of the calm category constituted the visual music and the vocal music immersion based on the vocal music emotional regression model of “combining multimedia information technology” was significantly enhanced when the emotional type of the music and the emotional type of the dynamic picture of the visual music was the same. This study carries out college vocal music teaching based on students’ emotional characteristics, which is of great significance to improve the quality of college vocal music teaching and students’ musical literacy.