Developing more resilient ASR algorithms and microphone designs is crucial in mitigating the impact of near-ultrasonic interference on voice-activated systems. Resilient ASR algorithms can be designed to incorporate advanced signal processing techniques and machine learning algorithms that can effectively filter out or mitigate the effects of near-ultrasonic noise. By enhancing the algorithms' ability to distinguish between legitimate voice commands and interference, the system can maintain accurate speech-to-text conversion even in the presence of disruptive ultrasonic frequencies. Additionally, improving microphone designs to be less prone to demodulating near-ultrasonic frequencies into the audible range can help reduce the vulnerability of voice-activated systems to such interference. By optimizing the microphone's frequency response and sensitivity characteristics, manufacturers can minimize the unintended effects of ultrasonic noise on the ASR process, thereby enhancing the system's overall robustness against malicious attacks exploiting this vulnerability.