Application of genetic algorithm in model music composition innovation

Abstract

Abstract The genetic algorithm-assisted musical composition combines evolutionary computational techniques and artistic composition. In this article, the evolution of musical compositions based on traditional genetic algorithm compositions is combined with interactive genetic algorithm techniques, mainly in model music innovation, using a genetic algorithm to generate an initial population with real number encoding of all individuals. The article focuses on studying the fitness function used to automatically evaluate the automatically generated melodies, perform evolutionary operations on the generated melodies, and generate high-quality model music melodies based on the treatment of evolutionary operations. The evaluation time of the generated melodies by the improved model is reduced from 4 minutes to 0.002 seconds, which makes the composer much more efficient in performing model music composition. The evaluation data of 16 pieces before and after the genetic manipulation were also compared, and it was found that the system evaluated the music after the genetic manipulation significantly higher than the music without the genetic manipulation. The different forms of musical compositions created by the composing system developed based on the technical research of computer genetic algorithm-assisted model music innovation are also a useful supplement to composers’ creations and open a new chapter for the field of artificial intelligence.