Abstract

The PAMGuard open-source software project was established in 2006 to provide a toolbox and app for the detection, classification, and localization (DCL) of bioacoustic signals. Releases typically attract between 1500 and 3500 downloads. Primarily developed for marine mammals, users can configure PAMGuard to work with a wide variety of hardware configurations (single hydrophones, to complex 3D arrays) and DCL algorithms, depending on the species of interest. A Java code base and integrated multi-threading allow multiple DCL algorithms to be run in parallel enabling rapid analysis of large acoustic datasets. A comprehensive data management system and a suite of interactive displays then allow users to visualize and annotate resulting data at temporal scales from milliseconds to years. This combination of advanced analysis algorithms and powerful data visualization in both real-time, or reviewing data post-hoc, means PAMGuard provides both automatic and a proven and reliable human-in-the-loop approach to analysis. Developers can use the program’s infrastructure to rapidly develop and deploy new algorithms; recently, an international collaboration has improved support for terrestrial species and developed a new module to import acoustic deep learning models, enabling users to take advantage of PAMGuard’s data management and visualization capabilities alongside the latest automated acoustic classifiers.

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