Make www.adultcybermart.com your daily reading habit

from www.escapistmagazine.com – The newest anti-smut technology not only watches what’s on your screen, but listens for the smacking, moaning, and smooth jazz synth sounds of pornography.

It’s good to see science has its priorities straight. Yeah, teleporters and clinical immortality would be cool, but what’s really important is keeping the lonely and sexually frustrated masses from checking out “Hot Co-Eds in Hot Tub Part 1” at work.

To that end, researchers at Korea Advanced Institute of Science and Technology in South Korea have developed software that can distinguish the not-so-subtle sounds of porn from everyday sounds, and block the offending content.

The program works by taking clips half a second in length and analyzing them with a technique called the Radon Transform. While speech generally consists of low pitches and music goes all over the place, porn consists of generally high pitches that fluctuate quickly and in repeating patterns. To build up a statistically significant pile of data representing the sort of sound patterns porn has, the researchers had to “analyze” truly epic amounts of online porn. Y’know, for “research.”

But all that mastur… er, “compiling of data” has paid off, and the software can now determine what is porn and what isn’t to an accuracy of 93 percent. The ones it got wrong often had loud background music or other confusing sounds, proving that even emotionless machines are confused by smooth jazz.

from www.popsci.com – A pair of South Korean electrical engineers have worked out a new porn filter that analyzes audio for tell-tale signs of things you really shouldn’t be watching at work. By using sound, they avoid the problem of visual porn-identifiers (pornifiers) that can get tricked by any expanse of skin, as in closeups of the face or other not-inappropriate body parts.

The engineers started by making spectrograms, basically a visual representation of a sound clip, of lots of different kinds of audio, including music, non-porn video, and porn. By analyzing these spectrograms, they figured out that pornographic audio has a few unique qualities that make it fairly easy to recognize: Regular speech is low-pitched, music has lots of different pitches, and both tend to be fairly constant. But the porn spectrograms showed a high pitch that changes often and also repeats itself.

Using this data, the engineers developed software that could identify porn correctly about 93% of the time. There were some hiccups; apparently laugh-tracked sitcoms sound like porn (weird fact!) and porn can sometimes sneak by the censors by using background music. Of course, image-recognition porn identifiers are just about as accurate and require much less time to analyze (a single frame, versus the audio identifier’s need for a longer clip). But it doesn’t necessarily need to be one or the other: Some see a potential to combine the audio and visual identifiers into one super-detector, a gauntlet through which no porn can pass.