On Saturday 23 February 2008, Sebastian Tschöpel wrote:> > - we are able to collect and compute all the necessary information> > with our senses and brain to perform this "switch off" ( i doubt> > that ) > > mmhmm.... maybe i shouldn't use such a superlative like "i doubt> that" here :) But it's definitely not a piece of cake, i never heard> of someone who can do such a thing and okay: There is a lot more to> our brain than what I can think of - haha! thats like a dog hunting> his own tail :) I think that would be a matter of training, basically; much like many people can "hear" what something will sound like before playing it. Untrained ears have a much harder time picking out and following individual instruments from a mix, but this is something that improves over time, in my experience. It's a lot like learning to read by recognizing the words rather than the individual letters. It would seem like the same basic mechanisms at play, though I don't know if that's actually how the human brain implements it. Now, theoretically, if you can make out the individual instruments from a mix, and know what these instruments would sound like on their own, you should basically be able to recreate any combination of these instruments in your mind. Anyway, from the strictly technical POV, there's this major overlapping problem. Getting the individual frequency components out of a fragment of music is trivial (relatively speaking) - but how do you know which ones go with what instrument? Well, consider a simple example with a solo melody voice over a simple bass line. As long as you can make out the fundamentals (which can turn out to be quite hard enough in real applications!), you can look at the spectrum and figure out which components follow what melody. This would require multipple analysis passes (to learn the instrument sounds and melodies), and/or a database of "familiar sounds"; it's not something you can just do frame by frame on unknown data. ...and of course, there's a million "minor" issues around this that make it a lot harder than it appears to be. Logically, it has to be possible, but maybe the first step would be to dispell a few confusing myths about how the human brain does this stuff. I think the brain has access to a lot of data that algorithms of this sort generally don't have. For example, I don't think it's realistically possible to do this without some sort of database of "familiar sounds", and/or some model of how the "average musically trained" human brain infers fundamentals from audible spectra. (There are plenty of instruments that have very little energy around the fundamental frequency, which makes even "simple" pitch tracking non-trivial.) Considering how the brain appears to work, I don't think there's a strict distinction between a "database" and a "model" in this regard. A neural network might be the proper model for software, and it's state after appropriate training would be the "database." //David Olofson - Programmer, Composer, Open Source Advocate .------- http://olofson.net - Games, SDL examples -------.| http://zeespace.net - 2.5D rendering engine || http://audiality.org - Music/audio engine || http://eel.olofson.net - Real time scripting |'-- http://www.reologica.se - Rheology instrumentation --'_______________________________________________Linux-audio-user mailing listLinux-audio-user@xxxxxxxxxxxxxxxxxxxxxxxx://lists.linuxaudio.org/mailman/listinfo/linux-audio-user
