Where can I find legally usable datasets for advanced audio chord recognition? [D]

I’m researching how to build or fine-tune an audio-to-chord-recognition engine comparable in ambition to Song Master Pro / Auralis Sound Prism. The goal is not basic major/minor chord detection. I need reliable recognition of dense harmonic material: jazz, soul, funk, neo-soul, Brazilian music, film music, and arrangements with chords such as maj9, 6/9, m9, m11, 13, altered dominants, slash chords/inversions, secondary dominants, modal interchange, suspensions, passing harmony, etc. Most public datasets I’ve found seem too limited: either simplified chord labels, weak annotations, or repertoire that does not really cover sophisticated harmony. In particular, I need time-aligned audio + chord labels, ideally with beat/downbeat information and a rich, consistent chord vocabulary. My questions: Which open datasets are genuinely useful for this level of chord-recognition work? Are there any commercial/licensable datasets with high-quality, detailed chord annotations that can legally be used to train a model and ship it in commercial software? Is a dataset such as iReal Pro-style chord charts, Hooktheory, Ultimate Guitar, Chordify, or similar usable in any legitimate/licensable way — or are they generally not viable due to rights and annotation quality? For a serious model, is the realistic route to combine public datasets with a privately licensed/hand-annotated corpus? If so, roughly how many accurately annotated tracks would be needed before it becomes meaningfully good at jazz-influenced harmony? Are there papers, benchmarks, companies, or dataset vendors I should study before spending money? I’m specifically looking for practical, legally usable data sources—not advice to scrape chord sites. Any experience from people who have trained MIR / chord-recognition models would be very valuable.