AI learns how to fool text-to-speech. That's bad news for voice assistants

A pair of computer scientists at the University of California, Berkeley developed an AI-based attack that targets speech-to-text systems. With their method, no matter what an audio file sounds like, the text output will be whatever the attacker wants it to be. This one is pretty cool, but it's also another entry for the "terrifying uses of AI" category. The team, Nicholas Carlini and Professor David Wagner, were able to trick Mozilla's popular DeepSpeech open-source speech-to-text system by, essentially, turning it on itself. Given any audio waveform, we can produce another that is over 99.9% similar, but transcribes as any phrase we choose (at a rate of up to 50 characters per second) … Our attack works with 100% success, regardless of the desired transcription, or initial source phrase being spoken.