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Comment by thangalin | Hacker News Reader

Slightly off-topic. Now that 1920s jazz music is falling into public domain, has anyone tried to reinvigorate the music using AI and generative adversarial approaches? Pre-1940s music didn't have high-fidelity sound, so the strong bass lines weren't captured. In theory, we could "downgrade" modern recordings to sound like 1920s recordings, then use adversarial techniques to train the machine on how to restore the antique recordings. Anyone know of any work being done in this area?

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It might be easier than that. Are the bass lines totally missing or are they just very weak? If you can capture a recording using vintage equipment and the placing of it, you can get the system response. Run the original recordings through an inversion of the response and you should get really close. Another possible method is to find the transform between an identical modern recording of the song and use the difference between the two recordings to make your transform.

> Are the bass lines totally missing or are they just very weak?

I think it might be that it's missing a large part of the lower frequencies, not that entire bass sound is missing. And I guess it'd be hard to faith-fully regenerate those, if we simply don't have a lot of samples.

Neither. You can hear them if you listen carefully, just the recording tech plus lack of amplification makes it harder than modern music.[1]

Source: have degree and postgrad in jazz and used to be a bass player. Have made transcriptions of early bass players from original recordings. (by ear without any kind of fancy tech)

[1] and the playing technique for various reasons.

The problem might be more complicated. In those times, they might not use a separate mic for every instrument (and the mics probably were not great), they might might not do the mastering properly, the amps could distort the sound, and instruments could overlap each other. And if you try to simply amplify lower frequencies, you might end up getting too much noise.

Some examples:

The Mooche

* https://www.youtube.com/watch?v=BPJ5vNmVL3I (The Duke, 1928)

* https://www.youtube.com/watch?v=tLdCq2PKM4o (John Barry, 1984)

Sugar Foot Stomp

* https://www.youtube.com/watch?v=qEdIWVsfPXs (Henderson, 1925)

* https://www.youtube.com/watch?v=35foefTrdLo (Nighthawks, 1993)

Doctor Jazz

* https://www.youtube.com/watch?v=HTYAaX7lqjQ (Morton, 1926)

* https://www.shazam.com/song/1687138286/doctor-jazz (Asaro & Fat Babies, 2016)

I was wondering if anyone was working on this (i.e., using pure software). Period equipment, real musicians, and such would be time consuming, arduous, and cost prohibitive.

So the idea would be to reconstruct the low frequency components from whatever upper harmonics are left in the recording? If you know the instruments and positioning of the recording device and something of its(the instruments, recorder, environment, etc.) characteristics, it might be possible to solve that using classic methods. There would be huge numbers of parameters, it is an interesting thought. Is there a large easily/freely available corpus of those recordings?

To do this, I think you are right that you would need to 'downgrade' modern recordings to sound old so that you have both sides of the training data covered.

This would be a cool project to work on. Ideally you would buy some vintage gear and then run the audio through both, but that would be very expensive. You could may be find some vst emulations though and get decent results.

The problem is AI "improvisation".

I could take my sequencer and crank the tempo up to a level on a Chopin etude that would smoke Yuja Wang too.

Who cares? The performance that is interesting is a human performance under these artistic constraints.

We didn't need transformers for algorithmic jazz or algorithmic composition in general.

It is also the bullshit of algorithmic Bach. Bach produced 1,100 works and most people haven't listened to even 1% of arguably the greatest artist who ever lived. What is the point of generating more?

There are plenty of current human bands that play this music really well though...

Just giggling silently as I imagine the stereotypical trad jazz purist's response to OP. Man, those guys are... Uhhh... Loyal to that vision of music.

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