Reconstructing Intelligible Speech from the Pressure Sensor Data in HVACs

Abstract: Pressure sensors are an integrated component of modern Heating, Ventilation, and Air Conditioning (HVAC) systems. As these pressure sensors operate within the 0-10 Pa range, support high sampling frequencies of 0.5-2 kHz, and are often placed close to human proximity, they can be used to eavesdrop on confidential conversation, since human speech has a similar audible range of 0-10 Pa and a bandwidth of 4 kHz for intelligible quality. This paper presents WaLi, which reconstructs intelligible speech from the low-resolution and noisy pressure sensor data by providing the following technical contributions: (i) WaLi reconstructs intelligible speech from a minimum of 0.5 kHz sampling frequency of pressure sensors, whereas previous work can only detect hot words/phrases. WaLi uses complex-valued conformer and Complex Global Attention Block (CGAB) to capture inter-phoneme and intra-phoneme dependencies that exist in the low-resolution pressure sensor data. (ii) WaLi handles the transient noise injected from HVAC fans and duct vibrations, by reconstructing both the clean magnitude and phase of the missing frequencies of the low-frequency aliased components. Extensive measurement studies on real-world pressure sensors show an LSD of 1.24 and NISQA-MOS of 1.78 for 0.5 kHz to 8 kHz upsampling. We believe that such levels of accuracy pose a significant threat when viewed from a privacy perspective that has not been addressed before for pressure sensors.