There is no such dataset out there. This way of thinking is a very self-limiting approach.

In my case, I built my own, through 10 years of organic instrumental input for the system to chomp through.

That's how you apply machine learning to the discipline of music.

The skill of making music well enough that I can trust a machine to emulate my style is unfortunately absent in me. Your response is not only patronizing but also loaded with false premise.

It's also apparently wrong: https://magenta.tensorflow.org/datasets

Thanks for your contribution.

That's too bad that it's absent in you. Maybe you should try to be a musician first, before trying to master AI-assisted music-making.

You say that I am applying a false premise and that I am apparently wrong -- but what kind of nonsense have those datasets output that comes even close to what I [0] have?

Also, you strongly misunderstand the value of having to build your own dataset of actual human input to achieve anything good in AI-assisted music-making. Good musical AI does not simply seek to mimic a dataset. That's such a pedantic oversimplification of this noble, difficult task that those of us who actually care about this issue face.

This problem cannot be solved like an object detection problem. You have a lot to learn before you start trying to insult those of us who have devoted much of our lives to the "problem" of AI in music.

This is art, buddy. Stay away from it if you are going to treat it like a mindless AI researcher at some institution.

[0] https://sonicmultiplicities.audio