But an automated speaker identification system might be looking at the same features that the voice-morphing software changes. In that case, it might not be useful except possibly for having a larger training corpus.
— Mike > On Jan 4, 2015, at 12:18 PM, Alfonso De Gregorio <[email protected]> wrote: > > > On Jan 1, 2015 8:34 PM, "Joseph Bonneau" <[email protected] > <mailto:[email protected]>> wrote: > ... > > Shirvanian/Saxena's experiments found that untrained human subjects had no > > more capacity to distinguish between a "true" voice and a morphed voice > > than between a "true" voice and a "true" voice with different background > > noise. They also point out some other attack avenues-if you get enough of > > Alice's audio (for example, if you're reading a hex fingerprint) you don't > > even have to synthesize, just re-order samples you already have. And often > > in one direction you only need to synthesize "yes" or "looks good" if both > > parties don't read the fingerprint > > I wonder: what is the false positive rate of a text independent automatic > speaker identification system? Can it perform any better than human subjects > in the same operative setting? If yes, can the user run such system inline > and enlist on its help to detect a MitM attack? > > More fundamentally, if the offense converts a crypto problem into an AI > problem should we turn to AI to defend? > > Alfonso > > _______________________________________________ > Messaging mailing list > [email protected] > https://moderncrypto.org/mailman/listinfo/messaging
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