Acoustic feature analysis of directional sound from parametric array speakers with application to mitigate attacks on voice-activated systems

A number of studies have identified the vulnerabilities of voice-activated devices to attacks from amplitude-demodulated sound from directional speakers. In this research, a controlled set of speech data, both live and played back from directional speakers, is analyzed to identify the acoustic features integral to speaker recognition in smart devices. A category of features, including Mel-frequency cepstral coefficients derived from Mel filter banks, are examined for potential to differentiate and classify speech sources. Potential vulnerabilities in voice-activated systems are systematically identified by examining the acoustic characteristics of diverse voice samples. This analytical approach aims to unveil potential weaknesses that could be exploited, triggering responses from these systems. The findings of this study contribute to the comprehension of the security landscape surrounding voice-activated technologies, paving the way for enhanced cybersecurity measures within this domain.