Efficient multichannel detection of impulsive audio events for wireless networks
| Autor: | Héctor A. Sánchez-Hevia, Roberto Gil-Pita, Manuel Rosa-Zurera |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
010302 applied physics
Acoustics and Ultrasonics Computer science Wireless network business.industry Feature vector Real-time computing Detector Antenna diversity 01 natural sciences 0103 physical sciences Path (graph theory) Wireless Spatial dependence business 010301 acoustics Wireless sensor network |
| Zdroj: | Applied Acoustics. 179:108005 |
| ISSN: | 0003-682X |
| DOI: | 10.1016/j.apacoust.2021.108005 |
| Popis: | Impulsive audio events such as gunshots, explosions or glass shattering, are commonly associated with security threats, thus they are of particular interest for automated acoustic surveillance. Even though impulsive audio events are greatly influenced by their propagation path, little work has been done in multichannel detection, and most precedents available in the literature deal with single-channel detection systems. Unfortunately, the spatial dependence of impulsive sound recordings proves as a problem for robust performance under real conditions. It is possible, however, to take advantage of the spatial diversity provided by a wireless sensor network to counteract this problem. In this paper, we show how an ensemble of spatially diverse detectors can greatly improve the performance of the system. We propose an efficient multichannel detection system of impulsive audio events intended for low-cost Wireless Acoustic Sensor Networks. Our proposal is based on a low complexity classification algorithm and an efficient method to include temporal context into the feature vector. The obtained results show that the proposed detection system is capable of achieving a more than adequate performance without incurring large computational loads. |
| Databáze: | OpenAIRE |
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