Soundscape classification with convolutional neural networks reveals temporal and geographic patterns in ecoacoustic data

Soundscape classification with convolutional neural networks reveals temporal and geographic patterns in ecoacoustic data

Interest in ecoacoustics has resulted in an influx of acoustic data and novel methodologies to classify and relate landscape sound activity to biodiversity and ecosystem health. However, indicators used to summarize sound and quantify the effects of disturbances on biodiversity can be inconsistent w...

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Bibliographic Details
Main Authors: Colin A. Quinn, Patrick Burns, Gurman Gill, Shrishail Baligar, Rose L. Snyder, Leonardo Salas, Scott J. Goetz, Matthew L. Clark
Format: Article
Language:English
Published: Elsevier 2022-05-01
Series:Ecological Indicators
Subjects:
Machine learning
Convolutional neural network (CNN)
Ecoacoustics
Anthropophony
Biophony
Naturally quiet landscapes
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X22003028

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http://www.sciencedirect.com/science/article/pii/S1470160X22003028

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