Inferring pre-defined Hierarchical Wave Function Collapse constraints from MIDI files
C. van den Oudenhoven (TU Delft - Electrical Engineering, Mathematics and Computer Science)
R. Bidarra – Mentor (TU Delft - Computer Graphics and Visualisation)
Joana Gonçalves – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
AI-generated music is a huge research field with many different approaches and models being the result of it. One such model is the ProceduraLiszt model, which utilizes the Wave Function Collapse algorithm, an algorithm similar to constraint programming, to generate its music. This research builds upon that model. It does so by trying to reverse engineer a given piece of music into a set of satisfied constraints that the model is compatible with. We present an approach that allows for the inference of constraints of a given music file that adheres to the MIDI format called MidiAnalyser. We run our model on a set of music files and analyze the inferred constraints. The constraints include aspects like key and note range.