Blur elimination is usually done with unsharp mask, which works by blurring raster even more and comparing to the original. The output makes the edges more shar

Blur elimination is usually done with unsharp mask, which works by blurring raster even more and comparing to the original. The output makes the edges more sharp but some information is lost anyway. Reverb elimination can be done without losses, just with distortions depending on the implementation. To do that, one have to recover cepstral[1] coefficients (with NN) and feed them to spectral filters (no NN needed). This is feasible, provided somebody prepares a training data set consisting of lots of pairs (sound, same_sound_with_reverb), where sound would be a voice, instrument, applause, etc. and with a different reverb settings. Very likely you'll have to use enormous sample rates, way beyond 44100, because you're supposed to deal with infinitesimal impulse response... Adds up to hardware requirements. I feel like I've oversimplified something, but it can be done, just lots of fidgeting with all the training sets and a training process itself. [1] https://en.wikipedia.org/wiki/Cepstrum https://en.wikipedia.org/wiki/Cepstrum