Practical Exploration on the Construction of Theoretical Courses of Composition Technology in the Age of Artificial Intelligence

Abstract

The theory of composition technology is to study the basic knowledge and skills of musicology, instrumental music, composition, and composition technology, including harmony, polyphony, musical form, orchestration, and so on, and then to analyze, create, and edit music. The current theory of composition technology has resulted in the phenomenon of relatively single form. The current method is the traditional way of composing music through the creation of composers. The defect is that various elements cannot be integrated together, and the meaning of music cannot be perfectly presented. In order to solve these problems, this paper proposes the use of recurrent neural network algorithm and backpropagation algorithm in artificial intelligence algorithm. It aims to study how to innovatively integrate the composition technology theory course with the current network technology. And it utilizes recurrent neural networks in artificial intelligence to help design part of the analysis of musical characteristics, through the evaluation of the music effect generated by automatic composition. The results show that the accuracy of note prediction obtained by the automatic composition method on the basis of objective evaluation is 81.93%, 90.15%, and 92.62%, respectively, on Top1, Top2, and Top3, which basically meet the current basic requirements for composition technology theory.