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Open-sourcing AudioCraft: Generative AI for audio

ai.meta.com

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Re: Open-sourcing AudioCraft: Generative AI for audio

#91

Post by NegativeK »

kmeisthax wrote: post #81
eropple wrote: post #34

Earlier quoted context omitted.

> MusicGen's weights are licensed CC-BY-NC, which is effectively a nonlicense as there is no noncommercial use you could make of an art generator How do you figure? Have you never just...made stuff to make stuff?

In copyright law the use of the work itself is considered a commercial benefit, so "noncommercial use" is an oxymoron. Consider these situations: - If I use AudioCraft to post freely-downloadable tracks on my SoundCloud, I still get the benefit of having a large audio catalog in my name, even if I'm not selling the individual tracks. I could later compose tracks on my own and ride off the exposure I got from posting…

Is listening at home a violation of NC? That's what I've interpreted as its intent.

Re: Open-sourcing AudioCraft: Generative AI for audio

#92

Post by PaulDavisThe1st »

manquer wrote: post #68
PaulDavisThe1st wrote: post #53

Earlier quoted context omitted.

[flagged]

Even before streaming, You never "owned" any music legally [1], you merely owned a physical copy of a performance[3] of a song, that in no way gives you the right to make derivative works [2] automatically. Also it doesn't really matter on what the law says, RIAA in the last iteration, relied on the fact it you would rather pay a fine than be able to afford expensive lawyers to fight the specifics out in court on ave…

Establishing derivation is at the crux of all legal matters surrounding diffusion models. It has not yet been clearly established. If it is, then I'd agree with you. Until then, I think it's a bit more up in the air.

Also, IIRC, RIAA did not bring many resources to bear against e.g. "home taping" itself, because they could essentially never know that it had occured. The overwhelming majority of their efforts went into trying to takedown people distributing multiple copies.

The Kashtanova case does not cover derivation in any real way, but is really about copyright attribution choices between human and software.

The Warhol case specifically tests a fair use claim, not a derivation claim.

Re: Open-sourcing AudioCraft: Generative AI for audio

#94

Post by emporas »

skybrian wrote: post #83

As an amateur musician I’m wondering if there are any of these audio generators that you can give a tune or chord progression to riff on. ABC format maybe? There are lots of folk tunes on thesession.org. Could you generate a rhythm track? Ideally you could make songs one track at a time, by giving it a mix of the previous tracks and asking it to make another track for an instrument. Or, give it a track and ask it to…

If you mean to give a source of melody of 30sec and extend that melody into a full song, yes MusicGen can do that. There are two ways to extend a song based on a melody: 1) give a sample, and continue the song from that sample as close as possible, and 2) give a melody as an inspiration.

They both work in varying degrees of success. Audiocraft on github, issues or discussion sections have a lot of questions answered.

Re: Open-sourcing AudioCraft: Generative AI for audio

#95

Post by NegativeK »

kmeisthax wrote: post #74
PaulDavisThe1st wrote: post #53

Earlier quoted context omitted.

[flagged]

Legal acquisition does not matter for AI training. If training is fair use then you can train on pirated material (e.g. OpenAI GPT). If it's not fair use then buying the material does not matter, you have to negotiate a specific license for AI training for each work in the training set, which is impractical at the scales most AI companies want to work.

The people above are arguing about being caught, not legality.

Re: Open-sourcing AudioCraft: Generative AI for audio

#96

Post by [deleted] »

manquer wrote: post #68
PaulDavisThe1st wrote: post #53

Earlier quoted context omitted.

[flagged]

Even before streaming, You never "owned" any music legally [1], you merely owned a physical copy of a performance[3] of a song, that in no way gives you the right to make derivative works [2] automatically. Also it doesn't really matter on what the law says, RIAA in the last iteration, relied on the fact it you would rather pay a fine than be able to afford expensive lawyers to fight the specifics out in court on ave…

[deleted]

Re: Open-sourcing AudioCraft: Generative AI for audio

#97

Post by mcbuilder »

ipaddr wrote: post #55
zyang wrote: post #44

Earlier quoted context omitted.

I was just thinking how Google made Android free to check Microsoft. This is Meta checking Google.

Checking OpenAI. Google is still playing checkers.

I just can't get how bad Google is doing. They have a ton of top researchers, papers, money, just no good LLMs. It's like OpenAI was first to the punch, and everyone else just saw $$$. Meta was smart to go down this open source road, as the masses will start training their llamas one way or another. Personally I believe the "intelligence" aspect will asymptote, so even having exclusive access to a "super AI" (i.e. hypothetical 1T parameter model like a GPT5) won't be that much of a step behind the lesser AIs, and as soon as you grant access to the masses they will start to use some transfer learning to make their "lesser" models better. AI applications though still need a lot of work. The models are smart or general purpose enough to be useful to the average person out of the box.

Re: Open-sourcing AudioCraft: Generative AI for audio

#98

Post by aedocw »

praveenhm wrote: post #87

does this model help in TTS(text-to-speech), badly needed only free option is bark and tortise TTS right now.

Coqui-TTS with vtck/vits is very good right now. Not as good as eleven labs or coqui studio, but for fast open TTS it's pretty good, in case you're not familiar with it.

It will be great when there's eventually something open that competes with the closed models out there.

Re: Open-sourcing AudioCraft: Generative AI for audio

#99

Post by JeremyNT »

gavman wrote: post #13

> MusicGen, which was trained with Meta-owned and specifically licensed music, generates music from text-based user inputs, while AudioGen, which was trained on public sound effects, generates audio from text-based user inputs. Meta is really clearly trying to differentiate themselves from OpenAI here. Open source + driving home "we don't use data we haven't paid for / don't own".

The fact that Meta is able to lie and call their restrictive licensing open source is nearly as misleading as "OpenAI."

We need to do better than to repeat these claims uncritically. The weight licenses are not "open source" by any useful definition, and we should not give Meta kudos for their misleading PR (especially considering that they almost surely ignored any copyright when training these things - rules for thee, but not for me).

"Not as closed as OpenAI" is accurate, but also damning with faint praise.

Re: Open-sourcing AudioCraft: Generative AI for audio

#100

Post by blackkettle »

sangnoir wrote: post #56
Culonavirus wrote: post #14

Here's a different question: Can you use the audio output this produces for anything else other than "research purposes"?

You can - as long as it's not commercial. It's a broad definition, but a good eule of thumb is if you're not directly making money out of the generated audio. They may still cone for you if you're making money indirectly, so consult a lawyer.

I can see some fantastic uses for this in generating complex acoustic environments to layer over TTS or real recordings for speech-to-text model training. I wonder if that is occupying some kind of gray-area. For example you have 1000hrs of clean speech from the librispeech corpus. It would be trivial to use this tool and available weights to generate background noise, environmental noise and the like, and then layer this with the clean speech to cheaply train a much more robust model. The environmental audio you create would never be directly shared or sold, but it would impact the overall quality of the STT model that you train from the combined results.
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