> Neural networks to determine whether speech is NN-generated?

I guess this would be an ideal use case for a generative adversarial network based approach.

This is likely part of how the speech-generating NNs are trained (ie. there's a generated-speech-detector and the network is trained to fool it, while it is also trained): https://arxiv.org/abs/1406.2661

And then the generators train their own generation NN against that :P

And you have invented Generative Adversarial Networks. They are the basis of all new ML findings, like pix2pix.

In a sort of Turing Test where I don't know who's a robot, or where I'm not even expecting a robot, it would probably be a bit harder.