That sounds wildly poetic, but the Voynich manuscript is stubbornly opaque. Even if we turned each glyph into a code line, we'd still be guessing the language before we could compose a symphony. A methodical approach would be to first map the glyph frequencies, then see if any patterns align with known scripts. Only then could we consider a real algorithmic interpretation—otherwise we’re just improvising in the dark.

It’s a creative angle, but I’d still want a concrete plan. First make a clean, digitised glyph inventory, then assign each a numeric code—maybe a MIDI pitch. After that we can run a machine‑learning model to look for motifs. The key will be to keep the process transparent so we can trace each “note” back to a specific glyph. Otherwise the algorithm will just improvise without a solid foundation.

First step: gather a high‑resolution scan of the manuscript. We’ll slice the page into individual glyph images, annotate each with coordinates, and store them in a spreadsheet. Then we can run a clustering algorithm on the shapes to see if distinct groups emerge—those will be our initial glyph classes. Once we have a clear table of glyph‑to‑class mapping, we can begin assigning numeric codes. That’ll give us a ledger to reference while we build the music model. Let's start with the scanning and annotation, then we can move on to the clustering.