What Does Perlin Noise Sound Like? (opens in new tab)

AFAIK iOS (and tvOS) devices only support playing formats+codecs with native hardware decoder support; they don't have any pure-CPU decoding implementations.

This, from what I recall, was an intentional choice to disincentivize developers from making the "easy choice" to ship assets in the same format+codec for all devices, where such a format would burn the iOS device's battery doing CPU decoding. Instead, most developers will choose to separately encode their assets for iOS, so that they can use the iOS media frameworks—which coincidentally means that they'll be using the efficient hardware encoding and not burning much battery at all.

However, you can ship custom CPU decoding in your app if you want (e.g. VLC.ipa).

Websites, obviously, aren't (usually) built for single architectures, though, so it's a bit of a pain for them. Larger web video providers (most porn sites, for example) keep iOS-specific encodings on their CDN and try to detect the browser's user agent to decide which version to deliver. Other providers just give up on the concept and build specific iOS-specific apps in order to ensure the correct media is delivered (this being why there are more "video-sharing site" apps for iOS than for Android.)

The concept of getting a panic attack in response to listening to some audio is completely foreign to me. Is it normal to have that reaction? It sure seems like it wouldn't be.

Thanks for the spectrograms! I'm not exactly sure which aliasing you're referring to... I'm trying to adjust the sampling rate of the noise function so that it maps to "real" seconds in a way that makes sense. By looking at the waveform in the audio editor, it looks exactly like a visual representation of 1D perlin noise to me (http://imgur.com/a/bM4tn). Looking at your spectrograms though, I'm seeing something in the higher-frequencies (and I think I can hear those as well), but I actually have no explanation for where those could have come from.

The code does explicitly assign a frequency of 440 Hz to the parameter rate in the first case and 110, 220, 440 Hz in the second. The second, fractal noise example might have been more interesting to compare to the first one if the author had kept the "fundamental" at 440 Hz and added higher-frequency overtones.