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Stable-Audio-Demo

stability-ai.github.io

151–160 of 249 posts

Re: Stable-Audio-Demo

#151

This is right into the "uncanny valley" of music. It definitely sounded "like music", but none of it is what a human would produce. There's just something off.

One thing I noticed is that when it’s playing chords, it seems a lot more likely than human players to put both major and minor thirds in. This isn’t unheard of — the famous Hendrix chord in “Purple Haze” consists of root, major third, 7th, minor third. But it sounds pretty weird when you do it in every chord.

Re: Stable-Audio-Demo

#152
post #103

Earlier quoted context omitted.

Website works fine on safari too, I didn’t notice any issues

Same, I wonder what issue they thought they had...

Safari is known to be troublesome when a webpage contains many HTML audio players. It can get extremely slow and unresponsive.

Every researcher I know in the audio domain uses Chrome for exactly that reason. The alternative would be not to use the standard HTML audio tag which would be ridiculous.

Re: Stable-Audio-Demo

#153
post #87
post #45

Earlier quoted context omitted.

Here is a silly song I generated using suno.ai, which I have found to be incredibly impressive (at least, a small percentage of its outputs are very good, most are bad). I think it's good enough that most humans wouldn't realise it's AI generated. https://app.suno.ai/song/8a64868d-9dd3-46db-91af-f962d4bec8b...

Wow. I’m guessing it’s generating MIDI or something rather than synthesizing audio from scratch? Even so, the quality of the score is leaps and bounds better than any of the long-form audio on the Stable Audio demo page (either Stable Audio itself or the other models). The audio model outputs seem to take a sequence of 1 to 3 chords, add a barebones melody on top, and basically loop this over and over. When they devi…

My understanding is that they use a side effect of the Bark model. The comment https://news.ycombinator.com/item?id=35647569 from JonathanFly probably explains it well. If you train your model on a massive amount of audio mixes of lyrics+music then prompting lyrics alone pulls the music with it as when the comment suggested that prompting context-correlated texts might pull the background noises usual for such context. Already while writing this I imagine training with a huge set of publicly performed poetry pieces that would allow generating novel performances of artificial poets with novel prompts. This is different to riffusion.com approach, where works the genius idea of more or less feeding spectrograms as images to Stable Diffusion.

Re: Stable-Audio-Demo

#154

Music without changes is boring. I enjoyed the much less stable results of OpenAI's JuleBox (2021?) more than any music AI to come since. Their sound quality is better but they only seem to produce one monotonous texture at a time.

As a musician, I found the pieces unremarkable. Of course, a lot of contemporary music is forgettable as well, as people try to create songs that all sound like hits but, in doing so, create uninteresting songs. I wonder what music the model is based on. I suppose for game music/sounds, perhaps its good enough?

Re: Stable-Audio-Demo

#155

> Warning: This website may not function properly on Safari. For the best experience, please use Google Chrome. We've come full circle with the 90's and Internet Explorer. Well I guess this time the dominant browser is opensource so that's atleast something... Can someone please create an animated GIF button for Chrome which says: "Best viewed with Google Chrome"?

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Re: Stable-Audio-Demo

#158
post #8

As with Stable Diffusion, text prompting will be the least controllable way to get useful output with this model. I can easily imagine midi being used as an input with control net to essentially get a neural synthesizer.

Yes. Since working on my AI melodies project ( https://www.melodies.ai/ ) two years ago, I've been saying that producing a high-quality, finalized song from text won't be feasible or even desirable for a while, and it's better to focus on using AI in various aspects of music making that support the artist's process.

Text will be an important input channel for texture, sound type, voice type and so on. You can't just use input audio, that defeats the point of generating something new. You can't also only use MIDI, it still needs to know what sits behind those notes, what performance, what instrument. So we need multiple channels.

Re: Stable-Audio-Demo

#159

Earlier quoted context omitted.

> If you require licensing fees for training data, you kill open source ML. And likely proprietary ML as well, hopefully. (To be clear, I think AI is an absolutely incredible innovation, capable of both good and harm; I also think it's not unreasonable to expect it to play a safer, slower strategy than the Uber "break the rules to grow fast until they catch up to you" playbook.) I'm all for eliminating copyright. Unt…

Bear with me here. Rushed and poorly articulated post incoming... In the broadest sense, generative AI helps achieve the same goals that copyleft licences aim for. A future where software isn't locked away in proprietary blobs and users are empowered to create, combine and modify software that they use. Copyleft uses IP law against itself to push people to share their work. Generative AI aims to assist in writing (or…

The majority of AI models out there (at least by popularity / capability) are proprietary; with weights and even model architectures that are treated as trade secret. Instead of having human-written music and movies that you legally can't copy, but practically can; you now have slop-generating models that live on a cloud server you have no control over. Artists and programmers who want to actually publish something - copyright or no - now have to compete with AI spam on search engines, while ChatGPT gets to merely be "confidently wrong" because it was built on the Internet equivalent of low-background metal - pre-AI training data. Generative AI is not a road that leads to less intellectual property[0], it's just an argument for reappropriating it to whoever has the fastest GPUs.

This is contrary to the goals of the Free Software movement - and also why Free Software people were the first to complain about all the copying going on. One of the things Generative AI is really good at is plagiarism - i.e. taking someone else's work and "rewriting it" in different words. If that's fair use, then copyleft is functionally useless.

It's important to keep in mind the difference between violating the letter of the law and opposing the business interests of the people who wrote the law. Copyleft and share-alike clauses have the intention of getting in the way of copyright as an institution, but it also relies on copyright to work, which is why the clauses have power even though they violate the spirit of copyright. Generative AI might violate the letter of the law, but it's very much in the spirit of what the law wants.

[0] Cory Doctorow: "Intellectual property is any law that allows you to dictate the conduct of your competitors"

Re: Stable-Audio-Demo

#160

Earlier quoted context omitted.

If I fly a plane and crash, my passengers die. If I generate an image using a model whose training included some unlicensed imagery... Disney misses out on a fraction of a cent? There is a real reason why some professions are licenced and others are not. Your analogy is nonsensical. Not having a better one is irrelevant.

If training data requires licensing fees, ML practitioners will become a licensed field de facto, because no one in the open source world will have the resources to pursue it on their own. Perhaps a better analogy is movies. At least with acting, you can make your own movies, even if you’re on a shoestring budget. With ML, you quite literally can’t make a useful model. There’s not enough uncopyrighted data to do anyt…

> If training data requires licensing fees, ML practitioners will become a licensed field de facto,

You know the word "license" has multiple, dissimilar meanings, right?

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