[vortico]

My ears think so too, but upsampling by just 2 is roughly the same difficulty as upsampling an image by 2. As you probably know, you can't just CIA-like "ENHANCE" an image to double its resolution and expect its noise level to be lower than, I don't know, 10 decibels (of image brightness). Yet our ears can notice noise as low as 40-50 decibels, so it would be nearly impossible to reconstruct higher frequencies so that the result has no noticeable noise.

In this research, the author is attempting to upsample by a bit more than 2.

[d--b]

That's the point of using deep learning here. Of course you can't make up the missing information, but by training the model with a lot of samples, it should eventually reach a point where it produces the most likely original information.

It works quite well on images: https://github.com/alexjc/neural-enhance

[charlesism]

    > you can't just CIA-like "ENHANCE" an image to 
    > double its resolution 

I think what you're saying is that if the high frequency information is gone, it's gone? But that shouldn't matter.. we don't need it to be identical to the original. It just needs to sound identical to the original.

If you hit a snare drum 5 times in a row, the high frequency data of each hit will differ wildly, and yet a human won't be able to tell the difference.