Gist 6fba698cb515db3002754ec29f820b5c

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Gist 6fba698cb515db3002754ec29f820b5c

✓ Published0🌍 Public

Last edited Jul 19, 2026

Created on Jul 19, 2026

This example demonstrates a workflow for validating musical data extracted from a MusicXML file against a manually created analysis CSV. The visualization compares four representations of a 12-bar trumpet melody—the original MusicXML score, a manual note/dynamics/slur analysis, an extracted text file, and a final JSON—to identify missing notes or performance details. A Python script parses the MusicXML into simplified text, and the JSON is prepared as control data for an AI sound-generation model. The gist highlights discrepancies between the files, treating the manual CSV as the reference, and invites feedback on ambiguities in the JSON annotations.

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