Thank you very much for the detailed answers. This clearly shows once again that things that sound relatively simple in theory are sometimes very difficult to implement.
To come back to the example with the applause. This was of course only an extreme example, which has been buzzing around in my head for quite some time. Only my idea was the following. It is possible, as Hans has already described correctly, to apply such neural networks to images. That works out pretty well in part. For example, some scientists have succeeded in removing rain from pictures.
Here's the article about it:
https://theoutline.com/post/979/scienti ... e-learning
That seems to work quite impressively. So I thought it should work somehow with audio material too. I only did a little bit of research and then came across the ISSE program. This was apparently a research project that included Adobe:
http://isse.sourceforge.net/
The exciting thing about this project is that in a relatively simple user interface, a complex algorithm is used to separate two sources from each other. This works out very impressively.
During my experimental phase I came up with this demanding example. You could try to separate the applause from the music. The approaches in the ISSE are not bad either, and you get rid of such noises relatively well. But what it mainly fails is of course the small data set. If you had 1000 test data with applause and the music, that would be much better. But one would probably need not only the pure applause but also a combination of music and applause, as well as pure music. That's going to be a lot.
Since I found this program I find it very exciting. Unfortunately, there are very few user-friendly programs to learn neural networks correctly. I sometimes find that far too technical and mathematical, and I don't quite understand the connections. maybe there is already some kind of technology that makes this possible, but I can't use it because I don't understand the constructively behind it.
just asked again purely obligatory. if you want to teach a neural network something, how do you choose the database? I imagine it to be relatively complex, because it seems to depend on details, as Hans has described correctly, based on the tank example. for me as a layman it would be interesting to try something like this. but the hurdles seem to be relatively high if you don't know your way around Matlab or Python.