Gibbons, Anthony and Donohue, Ian and Gorman, Courtney and King, Emma and Parnell, Andrew (2023) NEAL: an open-source tool for audio annotation. PeerJ, 11 (e15913). pp. 1-26. ISSN 2167-8359

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Abstract

Passive acoustic monitoring is used widely in ecology, biodiversity, and conservation studies. Data sets collected via acoustic monitoring are often extremely large and built to be processed automatically using artificial intelligence and machine learning models, which aim to replicate the work of domain experts. These models, being supervised learning algorithms, need to be trained on high quality annotations produced by experts. Since the experts are often resource-limited, a cost-effective process for annotating audio is needed to get maximal use out of the data. We present an open-source interactive audio data annotation tool, NEAL (Nature+Energy Audio Labeller). Built using R and the associated Shiny framework, the tool provides a reactive environment where users can quickly annotate audio files and adjust settings that automatically change the corresponding elements of the user interface. The app has been designed with the goal of having both expert birders and citizen scientists contribute to acoustic annotation projects. The popularity and flexibility of R programming in bioacoustics means that the Shiny app can be modified for other bird labelling data sets, or even to generic audio labelling tasks. We demonstrate the app by labelling data collected from wind farm sites across Ireland.

Item Type:	Article
Keywords:	Bioacoustics; Ecology; Audio annotation; Shiny app; Machine learning; Bioinformatics; Zoology;
Academic Unit:	Faculty of Science and Engineering > Mathematics and Statistics Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
Item ID:	18994
Identification Number:	https://doi.org/10.7717/peerj.15913
Depositing User:	Andrew Parnell
Date Deposited:	09 Oct 2024 13:59
Journal or Publication Title:	PeerJ
Publisher:	PeerJ
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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