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I can definitely hear issues with that phrase. It has quite robotic drop-offs.

Though coming soon: Neural networks to determine whether speech is NN-generated? :P




> 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.




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