A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets

The growing availability of long-term and large-scale passive acoustic recordings open the possibility of monitoring the vocal activity of elusive oceanic species, such as fin whales ( Balaenoptera physalus ), in order to acquire knowledge on their distribution, behavior, population structure and ab...

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Published in:Journal of Marine Science and Engineering
Main Authors: Elena Schall, Clea Parcerisas
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2022
Subjects:
Online Access:https://doi.org/10.3390/jmse10121831
https://doaj.org/article/5ca59ee6d04445d78489c14ff4d3bb50
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spelling ftdoajarticles:oai:doaj.org/article:5ca59ee6d04445d78489c14ff4d3bb50 2023-05-15T15:36:34+02:00 A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets Elena Schall Clea Parcerisas 2022-11-01T00:00:00Z https://doi.org/10.3390/jmse10121831 https://doaj.org/article/5ca59ee6d04445d78489c14ff4d3bb50 EN eng MDPI AG https://www.mdpi.com/2077-1312/10/12/1831 https://doaj.org/toc/2077-1312 doi:10.3390/jmse10121831 2077-1312 https://doaj.org/article/5ca59ee6d04445d78489c14ff4d3bb50 Journal of Marine Science and Engineering, Vol 10, Iss 1831, p 1831 (2022) fin whale Balaenoptera physalus automatic detection chorus 20 Hz pulse kurtosis Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581 article 2022 ftdoajarticles https://doi.org/10.3390/jmse10121831 2022-12-30T19:31:24Z The growing availability of long-term and large-scale passive acoustic recordings open the possibility of monitoring the vocal activity of elusive oceanic species, such as fin whales ( Balaenoptera physalus ), in order to acquire knowledge on their distribution, behavior, population structure and abundance. Fin whales produce low-frequency and high-intensity pulses, both as single vocalizations and as song sequences (only males) which can be detected over large distances. Numerous distant fin whales producing these pulses generate a so-called chorus, by spectrally and temporally overlapping single vocalizations. Both fin whale pulses and fin whale chorus provide a distinct source of information on fin whales present at different distances to the recording location. The manual review of vast amounts of passive acoustic data for the presence of single vocalizations and chorus by human experts is, however, time-consuming, often suffers from low reproducibility and in its entirety, it is practically impossible. In this publication, we present and compare robust algorithms for the automatic detection of fin whale choruses and pulses which yield good performance results (i.e., false positive rates < 3% and true positive rates > 76%) when applied to real-world passive acoustic datasets characterized by vast amounts of data, with only a small proportion of the data containing the target sounds, and diverse soundscapes from the Southern Ocean. Article in Journal/Newspaper Balaenoptera physalus Fin whale Southern Ocean Directory of Open Access Journals: DOAJ Articles Southern Ocean Journal of Marine Science and Engineering 10 12 1831
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic fin whale
Balaenoptera physalus
automatic detection
chorus
20 Hz pulse
kurtosis
Naval architecture. Shipbuilding. Marine engineering
VM1-989
Oceanography
GC1-1581
spellingShingle fin whale
Balaenoptera physalus
automatic detection
chorus
20 Hz pulse
kurtosis
Naval architecture. Shipbuilding. Marine engineering
VM1-989
Oceanography
GC1-1581
Elena Schall
Clea Parcerisas
A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets
topic_facet fin whale
Balaenoptera physalus
automatic detection
chorus
20 Hz pulse
kurtosis
Naval architecture. Shipbuilding. Marine engineering
VM1-989
Oceanography
GC1-1581
description The growing availability of long-term and large-scale passive acoustic recordings open the possibility of monitoring the vocal activity of elusive oceanic species, such as fin whales ( Balaenoptera physalus ), in order to acquire knowledge on their distribution, behavior, population structure and abundance. Fin whales produce low-frequency and high-intensity pulses, both as single vocalizations and as song sequences (only males) which can be detected over large distances. Numerous distant fin whales producing these pulses generate a so-called chorus, by spectrally and temporally overlapping single vocalizations. Both fin whale pulses and fin whale chorus provide a distinct source of information on fin whales present at different distances to the recording location. The manual review of vast amounts of passive acoustic data for the presence of single vocalizations and chorus by human experts is, however, time-consuming, often suffers from low reproducibility and in its entirety, it is practically impossible. In this publication, we present and compare robust algorithms for the automatic detection of fin whale choruses and pulses which yield good performance results (i.e., false positive rates < 3% and true positive rates > 76%) when applied to real-world passive acoustic datasets characterized by vast amounts of data, with only a small proportion of the data containing the target sounds, and diverse soundscapes from the Southern Ocean.
format Article in Journal/Newspaper
author Elena Schall
Clea Parcerisas
author_facet Elena Schall
Clea Parcerisas
author_sort Elena Schall
title A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets
title_short A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets
title_full A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets
title_fullStr A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets
title_full_unstemmed A Robust Method to Automatically Detect Fin Whale Acoustic Presence in Large and Diverse Passive Acoustic Datasets
title_sort robust method to automatically detect fin whale acoustic presence in large and diverse passive acoustic datasets
publisher MDPI AG
publishDate 2022
url https://doi.org/10.3390/jmse10121831
https://doaj.org/article/5ca59ee6d04445d78489c14ff4d3bb50
geographic Southern Ocean
geographic_facet Southern Ocean
genre Balaenoptera physalus
Fin whale
Southern Ocean
genre_facet Balaenoptera physalus
Fin whale
Southern Ocean
op_source Journal of Marine Science and Engineering, Vol 10, Iss 1831, p 1831 (2022)
op_relation https://www.mdpi.com/2077-1312/10/12/1831
https://doaj.org/toc/2077-1312
doi:10.3390/jmse10121831
2077-1312
https://doaj.org/article/5ca59ee6d04445d78489c14ff4d3bb50
op_doi https://doi.org/10.3390/jmse10121831
container_title Journal of Marine Science and Engineering
container_volume 10
container_issue 12
container_start_page 1831
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