This is one of variants of an area called "score following" and it's really hard. I remember about 10-15 years ago there was this craze in start-up land which led to many corpses of start-ups who thought solving semantic music problems would be easy with FFTs. But forgot to talk to an actual MIR (music information retrieval) or Musicologist. I remember a friend of mine working for one about 15 years ago and when she describe their deal I was like "have you talked to a real music person? Because that is only going to get you a tiny part of the way there". Nope. And sure enough, dead in the water a couple of years later. I'm studying music cognition right now in a cross discipline masters (music, comp sci) and it is crazy complicated.
In a nutshell: the human brain has an amazing ability to separate a garbage pail mush of audio into meaningful streams that we perceive as different event streams. This enabled us to do things like notice (as my prof says) the difference in white noise between the nearby river and the rustle in the leaves from something else, like an approaching animal. Score following requires doing this to separate the aggregate noise into different instruments and into voices within that instrument, suitable for note by note analysis. This, it turns out, is a wicked hard problem.