3 ms·

Not everything is magically fixable. That would involve creating elements that didn't exist at recording time or were removed by an encoder.

• andy_ppp 6y ago
  With enough training data I’m sure it can be done... I’ve seen CNNs that fill in 3D scenes and animate them from two images. I would guess this was a simpler problem?
  • andrewzah 6y ago
    Well, one thing to note is that humans spend more time processing audio than video. Bad audio is immediately noticeable and aggravating, compared to spotty video with clear audio. I -guess- CNNs can look at e.g. reduced frequency range recordings (like phone calls), and attempt to reconstruct them. However this seems like an arduous mountain to climb, as people's voices are unique. So are their environments and signal chains. I really doubt that something that generalized would work very well at reconstructing a specific person's voice and recording. This also gets into the problem that it would be constructing a new reality, not recreating it.
    • andy_ppp 6y ago
      Yes, you're probably right - I hadn't thought that the voice + noise is going to be one thing, extracting just the noise will be difficult, unique and maybe not trainable at all. I have thought about the constructing a new reality thing - I wouldn't be surprised if models ended up being trained to misspeak words which could get confusing...