Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems

Understand

Automatic speech recognition (ASR) systems can be fooled via targeted adversarial examples, which induce the ASR to produce arbitrary transcriptions in response to altered audio signals.

• However, state-of-the-art adversarial examples typically have to be fed into the ASR system directly, and are not successful when played in a room.
• The few published over-the-air adversarial examples fall into one of three categories: they are either handcrafted examples, they are so conspicuous that human listeners can easily recognize the target transcription once they are alerted to its content, or they require precise information about the room where the attack takes place, and are hence not transferable to other rooms.
• In this paper, we demonstrate the first algorithm that produces generic adversarial examples, which remain robust in an over-the-air attack that is not adapted to the specific environment.