[tsomctl]

Lol. When you superimpose noise, the original data is still there. When you have a FM radio playing staticky, heavily compressed music through crappy speakers in an acoustically terrible store and being captured by a terrible microphone and then being compressed, a significant amount of nonlinear distortion has taken place. That is extremely hard to model. And you would have to model it or have real data to train a neural network. Neural networks are extremely hard to train without excellent data.

[amelius]

> playing staticky, heavily compressed music through crappy speakers in an acoustically terrible store

I think you just confirmed how easy (and cheap) it is to actually generate this data.

[beachy]

If by "model" you mean reproduce, why is it so hard to simulate the distortion introduced by poor FM reception? Or by the acoustics of a store?

[d33]

I wonder if you could build a neural network that would do that...