Pressure sensors are widely integrated into modern Heating, Ventilation and Air Conditioning (HVAC) systems. As they are sensitive to acoustic pressure, they can be a source of eavesdropping. We introduce HVAC-EAR, which reconstructs intelligible speech from low-resolution, noisy pressure data with two key contributions: (i) We achieve intelligible reconstruction from as low as 0.5 kHz sampling rate, surpassing prior work limited to hot word detection, by employing a complex-valued conformer with a Complex Unifed Attention Block to capture phoneme dependencies; (ii) We mitigate transient HVAC noise by reconstructing both magnitude and phase of missing frequencies. For the first time, evaluations on real-world HVAC deployments show significant intelligibility up to 1.2 m distance, raising novel privacy concerns.

翻译：压力传感器在现代暖通空调系统中被广泛集成。由于其对声压敏感，可能成为窃听源。我们提出了HVAC-EAR，该系统能够从低分辨率、含噪声的压力数据中重建可理解的语音，其核心贡献包括：（i）通过采用带有复数统一注意力块的复数Conformer模型来捕捉音素依赖关系，我们实现了低至0.5 kHz采样率下的可理解语音重建，超越了先前仅限于热词检测的工作；（ii）通过重建缺失频率的幅度和相位，有效抑制了暖通空调系统的瞬态噪声。首次在真实世界暖通空调部署中的评估表明，在1.2米距离内仍能实现显著的可理解度，这引发了新的隐私担忧。