Procedural music generation with Hierarchical Wave Function Collapse

Abstract

Procedurally generating a coherent and emotionally resonant piece of music can be very challenging. The Wave Function Collapse (WFC) algorithm is very effective when it comes to generating randomized patterns and maps that resemble an input sample. A version of this algorithm using a hierarchy of sections, chords and melody was used to create a model capable of generating music. In this paper, we extend the capabilities of this model to improve its utility and help composers more effectively utilize this music generation method to create engaging pieces. Our model offers improvements over previous methods by allowing composers to retain desirable elements of the music output while regenerating others, thus streamlining the iterative nature of music composition. We consider and compare different music visualization techniques and explore various user interface (UI) interaction methods to facilitate the effective selection of elements from the output. We designed and implemented this model with the conclusion that it significantly enhances the user experience and allows for creating a much more sound and complete piece of music compared to the original.