[vanusa]

I would agree that the images are rather intriguing, but ... what does all this visual structure actually mean?

I'm guessing some kind of overtone structure in these sounds (perhaps decipherable to cats, but not to us)?

I await your insight.

[nixpulvis]

I know from personal experience, cat's use a lot of inflection in their voices. I'm not at all surprised by the images (though I don't know exactly what they mean). This inflection directly effects the image, because it modulates the pitch of the meow. Another factor, completely unrepresented in these images is the lower frequency components connected by seconds of silence. Most cats are pretty quiet, but sometimes they get the oral equivalent of the zoomies.

I would love to see more examples across species and variants of felines, under controlled conditions. Could you figure out an appropriate color map?

Not to start a dog vs cat war, but as someone who loves both, I think I can safely say that cats put much more information in their voices than dogs, for example.

[r00fus]

> Not to start a dog vs cat war, but as someone who loves both, I think I can safely say that cats put much more information in their voices than dogs, for example.

My cat only gets really vocal when she wants something ( & usually only with me, not my kids or spouse). She also trills a lot, usually in surprise. Could be they compress the data - dogs are very chatty - maybe the cats focus on high throughput whereas the dogs go for low-latency.

I'd love to see the same analysis done with dog barks.

[nixpulvis]

> maybe the cats focus on high throughput whereas the dogs go for low-latency.

I really like that way of thinking about it. Cats hit the low latency pretty quick with the hissing, which is what the wild cats looked more like in this projects demo. Kinda makes sense.

[gbh444g]

Interpreting ACF images:

1. Time progresses from the center to the edge of the circle.

2. Color means note, e.g. A4=432Hz is red, but so is A1, A2 and all other A notes. B is orange, C is yellow, D is green and so on.

3. The amount of fine details is frequency: the higher the frequency, the more fine details you see. If notes of different colors and different frequencies sound simultaneously, e.g. a A2 with a G5, you’ll see a red belt with a few repetitions mixed with a blue belt with 8x more repetitions, so the result will be a purple belt with a fine structure.

For example, on one image below there is a green belt with 10 repetitions. One repetition correponds to 13.5 Hz here (55296 Hz sample rate, 4096 FFT bins), so 10 repetitions is 135 Hz, which corresponds to C3. On another image there is a curious red cross in the center, it’s a red belt with 2 repetitons. That’s 27 Hz, or A0, almost infrasound.