Google is embedding inaudible watermarks into its AI generated music
theverge.com
theverge.com
It would not survive if you had an analysis package that could back compute the terms used by the model to generate the track and you re-generated the track with your own post processing, but that is a lot of work that most people would avoid.
It would be hilarious if someone built a model that you could query for it to tell you if there was subaudible information in the track and if so remove it (automating the above step to an AI task).
There have been projects that put subaudible tones in audio to trigger toys. So when you're watching a cartoon your toy would respond to the cartoon. Some people may, or may not, have considered doing something like that for muzak at businesses so that your phone OS could report back you had entered the business within a certain window of looking at an ad for that business.
There are tones, things you can hear typically in the range of 15 Hz to 22 kHz. When those tones vary in frequency over time by a few Hertz, it is unlikely that you can perceive that variation. Your ear is both logarithmic in its sensitivity to volume and not particularly sensitive to absolute frequency. If you shift an entire spectrum "up" a couple of Hz your ear won't notice, and similarly if you shift it "down" a couple of Hz you won't notice. This is especially true if you do it slowly (over the course of 100 milliseconds or so). Tape decks and turntables do this, they try to minimize it though. The specification that tells you how closely they track rotational speed is "Wow and Flutter" and a good number is < 0.3%, a studio recorder might be less than 0.1%.
With DSP you can easily pull out a spectrum shift of < 0.05% if it is 'regular'. That shift can be a "frequency shift keying" (FSK) signal with forward error correction in it. (think shifted 'up' as one (1) bits and shifted 'down' as zero (0) bits). Running the clip through an FFT and monitoring phase shift in the bins would recover this string of bits. And even if you didn't get enough to error correct the original message, their presence would be unmistakable.
All existing audio compression schemes do not affect the phase relationship of the spectrum they are compressing. That's a design feature.
To be fair, I wouldn't understand any of this if I hadn't been delving into software defined radio and learning DSP techniques for modulation and demodulation with data recovery in the presence of signal distortions and interference. And I completely understand that there is a language challenge when the terms 'audibly imperceptible' and 'inaudible' are treated as synonyms.
If I expect a 1kHz sine wave, and you transmit a signal that sounds imperceptibly no different than a pure 1khz sine wave (to a human ear), you could be encoding data in a signal that actually varies over time between 998hz and 1002 hz which could be extracted with DSP.
But, how would I extract a phase shift from an arbitrary novel music, for example [0], where I don't know what the expected reference is?
> Sitar for example, sounds very different and I believe its because they don't follow that practice
They still follow the same practice, maybe they don't center it on 440hz but the concept of tones and how far the steps between them are is the same all over the world, they just use different scales.
if there is information in the signal that is inaudible (tiny freq modulation), that information can be removed and greater compression will be achieved without loss of sound quality. So, perhaps mp3 doesn't do that, and perhaps it doesn't occur with enough frequency (hahaha) to make it worthwhile, but still, preservation is not guaranteed.
but TIL what you are talking about, useful, thanks
That makes the call center easier for both customer and agent and opens up the number of people who could be agents thus increasing competition and cutting costs to deliver call center service.
Imagine if Chinese companies masqueraded as American when they sell you phones and gadgets, or American companies masqueraded as Indonesian as they buy up their farmland.
Next we need to look at fixing the everyone can call everyone else with no pre approval. Smartphones could easily check the number against a list of people you have called before or phones vetted to be at hospitals or schools.
Businesses would want to disable it, but it would massively cut down on fraud.
Ai is not the problem.
Except the lack of watermark doesn't necessarily exclude the possibility of ai generation.
It has even been argued in court that a picture isn't tight evidence due to automatic processing, after all.
> Cinavia's in-band signaling introduces intentional spread spectrum phase distortion in the frequency domain of each individual audio channel separately, giving a per-channel digital signal that can yield up to around 0.2 bits per second.
> Cinavia is designed to stay within the audio signal and to survive all common forms of audio transfer, including lossy data compression using discrete cosine transform, MP3, DTS, or Ogg Vorbis. It is designed to survive digital and analog sound recording and reproduction via microphones, direct audio connections and broadcasting, and does so by using audio frequencies within the hearing range.
*#>Synth manufacturers start licking their lips.
And, for the amateur muso's that still don't get it: imagine having to pay/ have had paid for every time a dx7 was used in a tune, or an ms20?
But it's not audible in the sense that human ears can't discern it.
If an audio signal survives a lossy compression algorithm, then there are two possibilities:
- the compression algorithm should be improved, as it preserves some data that isn't important to the human ear
- the signal is audible
It's information theory. Either you can encode additional information without impacting the result, in which case the compression algorithm could use it to be more efficient, or you can't. TANSTAAFL.
There is an obvious third choice: the gain in compression isn't worth the effort of writing code to detect these non-discernible artifacts.
People are throwing around 0.2 bits/second in this thread. I doubt a company or individual would write code for such a trivial gain, never mind the slowdown in encoding it might cause.
Why wouldn’t it be worth it? You just have to write the code once and it will affect terabytes of music being compressed from that point forth.
I imagine this is also the case for audio watermarks, but I'm not sure what the current state of the art is for watermark removal.
This is primarily because those watermarks damage the image. The information about the content of the image beneath the watermark is missing (replaced with the watermark) and would have to be extrapolated or fabricated to replace it.
If the watermark isn't visible as part of the image then there is no missing piece to have to replace.
The watermark is applied to the spectrogram. Each "pixel" of the watermark represents a small band of frequency in a small time slice. The watermark presumably does something like increase the volume by 1% in the watermarked "pixels" -- basically imperceptibly adjusting EQ by tiny amounts in tiny places.
That will survive lossy compression just fine -- lossy compression applies a low pass filter and then removes whole spectrogram chunks where the signal is below a threshold.
But a watermark will still be entirely detectable in all the chunks that remain.
If you mean dynamic range compression, that's something done as part of mastering. It has nothing to do with DAC.
If you slightly alter the low frequency signals, they will be preserved. 30.1 Hz -> 30.2 Hz.
Quite certain that’s not true. We drop everything pass 20khz simply because it’s outside the average person’s hearing range.
We drop everything under 20hz too - we also cannot hear below that.
https://www.kaggle.com/code/therealcyberlord/watermark-remov...
Regenerating an audio is similar to painting a fake painting. It is the strokes which will reveal the original author. But in this case you want to claim the piece for yourself - stripping the signature elements of the author BUT still preserve the original quality.
So, make sure the ID is not more nuanced and distributed than you might think :) Otherwise your auto-encoder might reproduce it as well.
They are an important enabler of any potential harms for generative AI, because they provide a false sense of security, and the entities you should be most concerned about using generative AI to harm you will just use their own toolchains that don't put watermarks in, even if a regulatory regime is established effectively limiting public use to hosted systems which are compelled to use watermarks.
Depending on how much time/interest you have, https://c2pa.org/ has resources which explains more technical details about the process
Bob produces something with AI but claims he produced it himself and signs it with his private key.
AI produces something and signs it or doesn't, but if it's signed you can just throw the signature away and either publish it as unsigned or sign it again with a different key.
Signatures allow Alice to verify that something is signed by someone who has Bob's private key. If only Bob has Bob's private key, that means it was signed by Bob. It doesn't tell you whether it was generated by AI or not if Bob doesn't want you to know, because Bob can sign whatever he wants with his private key.
In this case "Bob" is presumably supposed to be some camera with DRM, but that means it will be in the physical control of attackers and anybody who can crack any camera by any manufacturer can extract the private key and use it to sign whatever they want, which is inevitably going to happen. Keys will be available for sale to anyone who wants one and doesn't have the technical acumen to extract one themselves. Since that makes the whole system worthless, what's the point?
Whether or not to trust Bob is an entirely different problem space than being able to prove an image came from Bob. In most scenarios Bob would be “trustworthy news source” who cares about their reputability. The important piece here is that if someone shares something on e.g. twitter and says Bob produced it, that claim can be verified.
> crack any camera by any manufacturer can extract the private key and use it to sign whatever they want, which is inevitably going to happen … Since that makes the whole system worthless, what's the point?
Think about what happens today when a private key is leaked - that key is no longer trusted. Will it be such a large scale problem such that the day any camera is released the keys are leaked? Maybe. Even in that scenario though we end up in the same spot as today except with the additional benefit of being able to verify stuff coming from NPR/CNN/your preferred news source that is shared on third party platforms.
We don't need some new system for that. You go to the website of your preferred news source and the connection is secured with TLS which certifies that the server is the one for the domain your browser shows you're visiting.
> Think about what happens today when a private key is leaked - that key is no longer trusted. Will it be such a large scale problem such that the day any camera is released the keys are leaked?
It's not that some camera's keys will be leaked and then you'll know not to trust them. It's that someone publishes how to extract the keys from some camera and then everything signed with any of those keys is called into question. Or figures out how to extract the keys from some camera or swipe them from one of the bureaucracies that generate them and doesn't tell anyone, they just use them to forge signatures.
And then because that is not only possible but likely to happen in practice, and you have no way to know when it has, you can't actually trust the signatures for anything.
Do you bank online? Public-private key encryption work well enough to support millions (billions?) of dollars worth of transactions per day - I don't think it's as broken as you make it seem
We've found a number of them, but the good ones are GPL3 [1]. I might email the authors about getting a license if there isn't anything equivalent.
[1] https://github.com/swesterfeld/audiowmark is fantastic
This is configurable, of course, but you sacrifice recoverability and/or quality of the original signal if you try to store more bits.
Neither a nor b are true so it’s probably fine.
- Non-bulletproof provenance data
- Non-bulletproof abuse tracking
- Non-bulletproof proliferation tracking
- Security sold to those concerned about AI
(I build an AI system, so these are all top of mind.)
But when you mark it they say "why u do that?"
You just can't win.
But then other people look at what they're proposing and say, "hey, you know this is a farce, right?"
Btw. audio compression is already doing most of the "stripping inaudible" stuff. You know, why wasting bits on something which is less likely to by picked up by the listener. It is done by assuming a model of human hearing.
Stable diffusion works great locally on both the dell+linux and the mac laptop I tried it on. This one was easy to use while exploring models from huggingface: https://diffusionbee.com/
DALL-E still gives better results, though.