Machine Learning-Based Improvement of Musical Digital Processing Technology on Musical Performance.

The modern stage focuses more on structural changes, and the numerical control technology realizes the complex changes of the stage scenes and the precise movement of stage props. The study object in this article is musical drama, and it uses digital technologies to digitally manipulate the soundtrack. This study offers a low-complexity feature space minimal variance algorithm that combines the power approach to address the concerns of inadequate resolution improvement, excessive complexity, poor real-time performance, and low resilience of standard MV methods. The method has a high resolution, low complexity, and great resilience, and it may be utilized in a variety of stages. In addition, this paper combines digital technology to process music, enhances the promotion of music in musical performances, and allows performers to integrate in more effectively. Finally, through experimental research, it can be known that the music digital processing technology proposed in this paper can play a good role in promoting musical performances. [ABSTRACT FROM AUTHOR]