Dear colleagues, On behalf of my co-authors I am pleased to announce that we have recently published an article in PLoS Computational Biology, describing a new open-source software called DetEdit for annotating and editing acoustic events. This paper is accessible online at: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.10075... The full reference and abstract are found below: Solsona-Berga A, Frasier KE, Baumann-Pickering S, Wiggins SM, Hildebrand JA (2020) DetEdit: A graphical user interface for annotating and editing events detected in long-term acoustic monitoring data. PLoS Comput Biol 16(1):e1007598. https://doi.org/10.1371/journal.pcbi.1007598 Abstract Passive acoustic monitoring has become an important data collection method, yielding massive datasets replete with biological, environmental and anthropogenic information. Automated signal detectors and classifiers are needed to identify events within these datasets, such as the presence of species-specific sounds or anthropogenic noise. These automated methods, however, are rarely a complete substitute for expert analyst review. The ability to visualize and annotate acoustic events efficiently can enhance scientific insights from large, previously intractable datasets. A MATLAB-based graphical user interface, called *DetEdit*, was developed to accelerate the editing and annotating of automated detections from extensive acoustic datasets. This tool is highly-configurable and multipurpose, with uses ranging from annotation and classification of individual signals or signal-clusters and evaluation of signal properties, to identification of false detections and false positive rate estimation. *DetEdit* allows users to step through acoustic events, displaying a range of signal features, including time series of received levels, long-term spectral averages, time intervals between detections, and scatter plots of peak frequency, RMS, and peak-to-peak received levels. Additionally, it displays either individual, or averaged sound pressure waveforms, and power spectra within each acoustic event. These views simultaneously provide analysts with signal-level detail and encounter-level context. *DetEdit* creates datasets of signal labels for further analyses, such as training classifiers and quantifying occurrence, abundances, or trends. Although designed for evaluating underwater-recorded odontocete echolocation click detections, *DetEdit* can be adapted to almost any stereotyped impulsive signal. Our software package complements available tools for the bioacoustic community and is provided open source at https://github.com/MarineBioAcousticsRC/DetEdit. -- Alba Solsona Berga Postdoctoral Researcher Scripps Institution of Oceanography University of California San Diego 9500 Gilman Drive #0205 La Jolla, CA 92093 Phone: (858) 246-2252 Email: asolsonaberga@ucsd.edu