A while ago I did a lot of research in this area. The answer is basically that the human ear is incredibly good at detecting "errors" while the human eye smooth

A while ago I did a lot of research in this area. The answer is basically that the human ear is incredibly good at detecting "errors" while the human eye smooths over them. You don't notice that the color of pixels are off, that some figures proportions are wrong, or that a face is all mush. But you do notice if a few notes are in the wrong key or if the rhythm is off in some beats. So your music model needs to be more conservative to not make errors but then it often falls into the trap of just repeating the same notes over and over or outputting the blandest elevator music you can think of. Or it just plagiarizes. E.g. takes the melody from a Fleetwood Mac song and combines it with some Rolling Stones drums and passes it off as its own. I'm convinced that image models also plagiarizes but that their plagiarism is much easier to mask. A song is still the same song even if you change the key, tempo, and timbre, but the equivalent operations applied to images are much harder to spot.