Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.

Passive acoustic monitoring (PAM) coupled with automated species identification is a promising tool for species monitoring and conservation worldwide. However, high false indications of presence are still an important limitation and a crucial factor for acceptance of these techniques in wildlife sur...

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Main Authors: Ivan Braga Campos, Todd J Landers, Kate D Lee, William George Lee, Megan R Friesen, Anne C Gaskett, Louis Ranjard
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0212727
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author Ivan Braga Campos
Todd J Landers
Kate D Lee
William George Lee
Megan R Friesen
Anne C Gaskett
Louis Ranjard
author_facet Ivan Braga Campos
Todd J Landers
Kate D Lee
William George Lee
Megan R Friesen
Anne C Gaskett
Louis Ranjard
author_sort Ivan Braga Campos
collection DOAJ
description Passive acoustic monitoring (PAM) coupled with automated species identification is a promising tool for species monitoring and conservation worldwide. However, high false indications of presence are still an important limitation and a crucial factor for acceptance of these techniques in wildlife surveys. Here we present the Assemblage of Focal Species Recognizers-AFSR, a novel approach for decreasing false positives and increasing models' precision in multispecies contexts. AFSR focusses on decreasing false positives by excluding unreliable sound file segments that are prone to misidentification. We used MatlabHTK, a hidden Markov models interface for bioacoustics analyses, for illustrating AFSR technique by comparing two approaches, 1) a multispecies recognizer where all species are identified simultaneously, and 2) an assemblage of focal species recognizers (AFSR), where several recognizers that each prioritise a single focal species are then summarised into a single output, according to a set of rules designed to exclude unreliable segments. Both approaches (the multispecies recognizer and AFSR) used the same sound files training dataset, but different processing workflow. We applied these recognisers to PAM recordings from a remote island colony with five seabird species and compared their outputs with manual species identifications. False positives and precision improved for all the five species when using AFSR, achieving remarkable 0% false positives and 100% precision for three of five seabird species, and < 6% false positives, and >90% precision for the other two species. AFSR' output was also used to generate daily calling activity patterns for each species. Instead of attempting to withdraw useful information from every fragment in a sound recording, AFSR prioritises more trustworthy information from sections with better quality data. AFSR can be applied to automated species identification from multispecies PAM recordings worldwide.
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spelling doaj.art-c28ed14011af4b989a8b47fa1e666ac82022-12-21T21:55:24ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011412e021272710.1371/journal.pone.0212727Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.Ivan Braga CamposTodd J LandersKate D LeeWilliam George LeeMegan R FriesenAnne C GaskettLouis RanjardPassive acoustic monitoring (PAM) coupled with automated species identification is a promising tool for species monitoring and conservation worldwide. However, high false indications of presence are still an important limitation and a crucial factor for acceptance of these techniques in wildlife surveys. Here we present the Assemblage of Focal Species Recognizers-AFSR, a novel approach for decreasing false positives and increasing models' precision in multispecies contexts. AFSR focusses on decreasing false positives by excluding unreliable sound file segments that are prone to misidentification. We used MatlabHTK, a hidden Markov models interface for bioacoustics analyses, for illustrating AFSR technique by comparing two approaches, 1) a multispecies recognizer where all species are identified simultaneously, and 2) an assemblage of focal species recognizers (AFSR), where several recognizers that each prioritise a single focal species are then summarised into a single output, according to a set of rules designed to exclude unreliable segments. Both approaches (the multispecies recognizer and AFSR) used the same sound files training dataset, but different processing workflow. We applied these recognisers to PAM recordings from a remote island colony with five seabird species and compared their outputs with manual species identifications. False positives and precision improved for all the five species when using AFSR, achieving remarkable 0% false positives and 100% precision for three of five seabird species, and < 6% false positives, and >90% precision for the other two species. AFSR' output was also used to generate daily calling activity patterns for each species. Instead of attempting to withdraw useful information from every fragment in a sound recording, AFSR prioritises more trustworthy information from sections with better quality data. AFSR can be applied to automated species identification from multispecies PAM recordings worldwide.https://doi.org/10.1371/journal.pone.0212727
spellingShingle Ivan Braga Campos
Todd J Landers
Kate D Lee
William George Lee
Megan R Friesen
Anne C Gaskett
Louis Ranjard
Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.
PLoS ONE
title Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.
title_full Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.
title_fullStr Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.
title_full_unstemmed Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.
title_short Assemblage of Focal Species Recognizers-AFSR: A technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context.
title_sort assemblage of focal species recognizers afsr a technique for decreasing false indications of presence from acoustic automatic identification in a multiple species context
url https://doi.org/10.1371/journal.pone.0212727
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