I'm sure they are more nuanced in that of course they will take into account differences in breadth etc. to some extent, but they are clearly not nuanced enough, because they barely work.
> Also, "genre" and "mood" of a piece of music are not easy to define, let alone measure. You're asking for a lot and I don't think what you're asking for is realistic from a piece of software.
Yet I think if you asked a bunch of humans to attach labels to tracks they like, you'd find they overlap closely enough.
I base that on the fact that while many will struggle to identify niche sub-genres or discriminate between genres they don't listen to, people certainly have a relatively large shared idea about major classifications.
What is more: You'd be able to find the labels of people who usually label the same way as you.
And it doesn't need to be precise. It just needs to better.
> Also, "genre" and "mood" of a piece of music are not easy to define, let alone measure. You're asking for a lot and I don't think what you're asking for is realistic from a piece of software.
Yet I think if you asked a bunch of humans to attach labels to tracks they like, you'd find they overlap closely enough.
I base that on the fact that while many will struggle to identify niche sub-genres or discriminate between genres they don't listen to, people certainly have a relatively large shared idea about major classifications.
What is more: You'd be able to find the labels of people who usually label the same way as you.
And it doesn't need to be precise. It just needs to better.