Hello, Audio Engineer with some little knowledge regarding AI here.
What you think of is restoring frequencies, this is possible, and commonly used in plugins for audio restaurization. I might be mistaken, but this does not improve the bitrate, but the perceived quality (which is still lossy).
I don’t think that there is a real interest to upscale quality (not perceived quality), especially for longer (> 1 minute) material.
It’s funny you say that. I, as most people bought a bunch of CDs back in the day and ripped a bunch before I gave up my CD drive. At the time, storage was expensive and so I did what I could at the time with MP3. As storage gets cheaper (though not cheap enough for me to go lossless), I’d like to be able to upscale my music while keeping a similar file size and have my collection mature with me until storage becomes cheap enough for me to go lossless.
You’re better off buying a cheap USB optical drive, re-ripping those CDs, and transcoding the files to something like Opus, which offers comparable quality to 320kbps MP3 files at lower bitrates (which also means smaller file sizes).
Or you can just “download” the FLAC versions, transcode those, and delete them after.
Also, kind of funny how this was posted just after someone complained about the same thing in the audio engineering subreddit.
Hmmm. I feel like this is one of those long-term studies that would be quite exciting? Am I wrong to be a little bit excited about programs learning how to guess correctly what should be where and subsequently how things should sound?
It cannot bring back lost data. It can hallucinate something that is statistically likely given the context but I’m not aware of any tool which can do that to a useful degree.
What’s the context? Why can’t you just get a better encode where the data isn’t lost?
Old mixtapes and such can be noisy with hizzes, pops and such. It is possible to filter out those artefacts but thats removing stuff, just as digitally compressing audio is removing stuff. You can’t create data from nowhere for digitally compressed files and you can’t simply add back the hizz, noise, and pops to the mixtapes if you remove that.
Basically something to improve quality. So from 192kbs to 320kbs
That’s not really possible, once compressed the original audio is just missing entirely.
Can AI not do in the same way that it does with pictures?
Hello, Audio Engineer with some little knowledge regarding AI here.
What you think of is restoring frequencies, this is possible, and commonly used in plugins for audio restaurization. I might be mistaken, but this does not improve the bitrate, but the perceived quality (which is still lossy).
I don’t think that there is a real interest to upscale quality (not perceived quality), especially for longer (> 1 minute) material.
It’s funny you say that. I, as most people bought a bunch of CDs back in the day and ripped a bunch before I gave up my CD drive. At the time, storage was expensive and so I did what I could at the time with MP3. As storage gets cheaper (though not cheap enough for me to go lossless), I’d like to be able to upscale my music while keeping a similar file size and have my collection mature with me until storage becomes cheap enough for me to go lossless.
I can’t be the only person who’s thought of this.
You’re better off buying a cheap USB optical drive, re-ripping those CDs, and transcoding the files to something like Opus, which offers comparable quality to 320kbps MP3 files at lower bitrates (which also means smaller file sizes).
Or you can just “download” the FLAC versions, transcode those, and delete them after.
Also, kind of funny how this was posted just after someone complained about the same thing in the audio engineering subreddit.
That is comedy gold! £1000 Ethernet cables? WTF?
wow, so now reddit won’t let you see the post without logging in even if you open it through the old.reddit domain?
This link should work.
I didn’t realize that reddit formats the link completely differently when you “share” from its shitty app.
My bad, and sorry about that. Should work now.
https://yewtu.be/watch?v=brLNcJeSAhw
It wouldn’t be the original audio, the AI would just be making up new content to fill in the blanks like it does with a photo.
That’s not a bad thing though, right?
If you’re OK listening to a derivative work of your input. Otherwise, it’s bad.
Hmmm. I feel like this is one of those long-term studies that would be quite exciting? Am I wrong to be a little bit excited about programs learning how to guess correctly what should be where and subsequently how things should sound?
you won’t magically restore the parts that have been removed during compression.
Can AI or machine learning not do in the same way that it does with pictures?
It cannot bring back lost data. It can hallucinate something that is statistically likely given the context but I’m not aware of any tool which can do that to a useful degree.
What’s the context? Why can’t you just get a better encode where the data isn’t lost?
Things like old mixtapes are impossible to get better encodes of
Old mixtapes and such can be noisy with hizzes, pops and such. It is possible to filter out those artefacts but thats removing stuff, just as digitally compressing audio is removing stuff. You can’t create data from nowhere for digitally compressed files and you can’t simply add back the hizz, noise, and pops to the mixtapes if you remove that.
Going from 192kbps to 320kbps would be audibly negligible unless you used a really bad codec to begin with.
Probably not even worth it, tbh.
Ah, thank you for the info