[ljclifford]

I'm unfamiliar with 'pornography recognition' as an established task in ML research (lol), but for what it's worth, it's not an innovate use of CNNs for audio classification. You can essentially turn any audio classification task into an image problem (raw audio into features like spectrograms/MFCCs). Which people have been doing since forever (by which I mean a number of years now).

[PaulHoule]

The question of it in my mind is if the available features are structurally adequate.

Porn videos frequently have a soundtrack with distinctive moaning and that's one thing. If the problem was distinguishing audio recordings of somebody talking about erotic or not-erotic subjects, that's something entirely different.

[sqeaky]

> 'pornography recognition' as an established task in ML research (lol),

Exactly my thought process. Maybe I should learn modern ML and apply my, ahem expertise, and apply for some grants.