Research on multi-system interactive pop music composition based on artificial intelligence technology

Abstract

The purpose of this paper is to analyze MIDI technology for pop music composition and the application of composition in artificial intelligence. Based on deep learning, a SeqVAE-based music melody generation algorithm is designed, the possibility of a pulse neural network-based music melody generation algorithm is explored, and a multi-system interactive pop music composition system is established and tested. This system's accuracy rate for bass and treble recognition was tested to be 4%, 4.1%, 2.47%, and 2.66, respectively, compared to the traditional recognition rate. The recommendation satisfaction rate was 96 when the number of queries was 50, the response speed increase time was less and kept within 3 seconds, and the CPU occupancy rate was within 40%.

Keywords

• midi technology
• seqvae algorithm
• impulsive neural network
• artificial intelligence
• multi-system interaction
• 97m80