Adaptive VR Test in Music Harmony Based on Conditional Spiking GAN

Abstract

This article proposes an adaptive VR test for the knowledge level control in music harmony. The core functioning relies on conditional semantic music generation strategy, using spiking conditional GAN architecture. The novel method of semantic music information encoding based on the system of graphs in music harmony, allowed two-dimensional data representation of harmonic sequences. which made possible considerable data augmentation and a transition to the specifics of training inherent to the visual domain. To our best knowledge, this is the first attempt of conditional spiking GAN implementation along with the application of the spiking neural networks in a domain of semantic music generation.