Chromesthetic Generative Music Visualiser

The Chromesthetic Generative Music Visualiser is an audiovisual system that maps musical structure to colour, texture, and motion in real time. Inspired by chromesthesia, it uses machine learning and procedural graphics to generate visuals that feel closely tied to the character of the music.

A neural network analyses features such as harmony, timbre, and rhythm, and outputs visual parameters that shape the scene’s colour palette, texture, and overall atmosphere. These are combined with procedural elements that more directly represent musical events.

For example, changes in key can drive shifts in the visual palette, while the density and character of the music influence the textures that emerge on screen. The output is organised across two layers: an ML-driven background visualiser and an algorithmic Note Stream that highlights melodic and harmonic activity.

The aim is not simply to create visuals that react to sound, but to build a coherent visual language that emerges from the music itself.