HVAC-EAR: Eavesdropping Human Speech Using HVAC Systems
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918374816088064 |
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| author | Tamiti, Tarikul Islam Joshi, Biraj Hasan, Rida Barua, Anomadarshi |
| author_facet | Tamiti, Tarikul Islam Joshi, Biraj Hasan, Rida Barua, Anomadarshi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_01082 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | HVAC-EAR: Eavesdropping Human Speech Using HVAC Systems Tamiti, Tarikul Islam Joshi, Biraj Hasan, Rida Barua, Anomadarshi Sound Cryptography and Security 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. |
| title | HVAC-EAR: Eavesdropping Human Speech Using HVAC Systems |
| topic | Sound Cryptography and Security |
| url | https://arxiv.org/abs/2510.01082 |