Clustering acoustic events in environmental recordings for species richness surveys

Eichinski, Philip, Sitbon, Laurianne, & Roe, Paul (2015) Clustering acoustic events in environmental recordings for species richness surveys. In Procedia Computer Science, Elsevier BV, Reykjavík, Iceland, pp. 640-649.

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Abstract

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets.

In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples.

Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Impact and interest:

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1 citations in Web of Science®

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ID Code: 86682
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: ecoacoustics, environmental monitoring, species richness, cluster analysis, acoustic events
DOI: 10.1016/j.procs.2015.05.178
ISSN: 1877-0509
Subjects: Australian and New Zealand Standard Research Classification > ENVIRONMENTAL SCIENCES (050000) > ENVIRONMENTAL SCIENCE AND MANAGEMENT (050200) > Environmental Monitoring (050206)
Australian and New Zealand Standard Research Classification > TECHNOLOGY (100000) > OTHER TECHNOLOGY (109900) > Technology not elsewhere classified (109999)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright © 2015 The Authors.
Deposited On: 20 Aug 2015 05:06
Last Modified: 26 Feb 2016 04:55

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