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DetEdit: A graphical user interface for annotating and editing events detected in long-term acoustic monitoring data

TitleDetEdit: A graphical user interface for annotating and editing events detected in long-term acoustic monitoring data
Publication TypeJournal Article
Year of Publication2020
AuthorsSolsona-Berga A., Frasier K.E, Baumann-Pickering S., Wiggins SM, Hildebrand JA
Volume16
Date Published2020/01
Type of ArticleArticle
ISBN Number1553-734X
Accession NumberWOS:000510916500037
KeywordsBiochemistry & Molecular Biology; Mathematical & Computational Biology
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.

DOI10.1371/journal.pcbi.1007598
Student Publication: 
No
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