  The widespread adoption of voice-activated systems has modified routine
human-machine interaction but has also introduced new vulnerabilities. This
paper investigates the susceptibility of automatic speech recognition (ASR)
algorithms in these systems to interference from near-ultrasonic noise.
Building upon prior research that demonstrated the ability of near-ultrasonic
frequencies (16 kHz - 22 kHz) to exploit the inherent properties of
microelectromechanical systems (MEMS) microphones, our study explores
alternative privacy enforcement means using this interference phenomenon. We
expose a critical vulnerability in the most common microphones used in modern
voice-activated devices, which inadvertently demodulate near-ultrasonic
frequencies into the audible spectrum, disrupting the ASR process. Through a
systematic analysis of the impact of near-ultrasonic noise on various ASR
systems, we demonstrate that this vulnerability is consistent across different
devices and under varying conditions, such as broadcast distance and specific
phoneme structures. Our findings highlight the need to develop robust
countermeasures to protect voice-activated systems from malicious exploitation
of this vulnerability. Furthermore, we explore the potential applications of
this phenomenon in enhancing privacy by disrupting unauthorized audio recording
or eavesdropping. This research underscores the importance of a comprehensive
approach to securing voice-activated systems, combining technological
innovation, responsible development practices, and informed policy decisions to
ensure the privacy and security of users in an increasingly connected world.
