gnn-audio-generation

Sonifying GNN models translates model states, transitions, and parameters into audible representations, enabling rapid understanding and communication of complex model dynamics for debugging, education, and research prototyping in active inference.

To generate audio from GNN markdown files, you need a GNN model markdown file as input and SAPF or Pedalboard backends to process states, transitions, and parameters into tonal, rhythmic, ambient, and sonification WAV artifacts.

Yes, GNN audio generation works with SAPF and Pedalboard backends to export WAV-based audio artifacts, mapping model structures, states, transitions, and parameters into tonal, rhythmic, ambient, and sonification audio outputs.

Yes, you can use sonification for educational demonstrations of active inference models by mapping GNN parameters and transitions to audio outputs, producing tonal, rhythmic, and ambient representations to illustrate model behavior for teaching and exploration.

The best way to sonify GNN states and transitions is passing GNN markdown to SAPF and Pedalboard backends, which map parameters to tonal, rhythmic, ambient, and sonification audio outputs for model inspection and research prototyping.