We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls

Autores
Barros de Araújo, Carlos
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The acousticmonitoring (PAM) of biodiversity has gained traction in recent years, even though classifying species within a recording could be challenging in places where acoustic diversity is high. Among the classification algorithms recently developed, BirdNET is probably the most promising. BirdNET was built to recognize over six thousand bird species and was trained using data from Xeno-canto and the Macaulay Library. Despite its huge potential, BirdNET is known to struggle with noisier recordings (1), reducing its accuracy for PAM.
Fil: Barros de Araújo, Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentina
Materia
bioacustica
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/257427
Acceder
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spelling We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcallsBarros de Araújo, Carlosbioacusticahttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The acousticmonitoring (PAM) of biodiversity has gained traction in recent years, even though classifying species within a recording could be challenging in places where acoustic diversity is high. Among the classification algorithms recently developed, BirdNET is probably the most promising. BirdNET was built to recognize over six thousand bird species and was trained using data from Xeno-canto and the Macaulay Library. Despite its huge potential, BirdNET is known to struggle with noisier recordings (1), reducing its accuracy for PAM.Fil: Barros de Araújo, Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; ArgentinaNational Academy of Sciences2024-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/257427Barros de Araújo, Carlos; We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls; National Academy of Sciences; Proceedings of the National Academy of Sciences of The United States of America; 121; 51; 12-2024; 1-10027-8424CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pnas.org/doi/10.1073/pnas.2419635121info:eu-repo/semantics/altIdentifier/doi/10.1073/pnas.2419635121info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:11:20Zoai:ri.conicet.gov.ar:11336/257427instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 12:11:20.631CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
title We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
spellingShingle We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
Barros de Araújo, Carlos
bioacustica
title_short We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
title_full We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
title_fullStr We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
title_full_unstemmed We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
title_sort We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls
dc.creator.none.fl_str_mv Barros de Araújo, Carlos
author Barros de Araújo, Carlos
author_facet Barros de Araújo, Carlos
author_role author
dc.subject.none.fl_str_mv bioacustica
topic bioacustica
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The acousticmonitoring (PAM) of biodiversity has gained traction in recent years, even though classifying species within a recording could be challenging in places where acoustic diversity is high. Among the classification algorithms recently developed, BirdNET is probably the most promising. BirdNET was built to recognize over six thousand bird species and was trained using data from Xeno-canto and the Macaulay Library. Despite its huge potential, BirdNET is known to struggle with noisier recordings (1), reducing its accuracy for PAM.
Fil: Barros de Araújo, Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentina
description The acousticmonitoring (PAM) of biodiversity has gained traction in recent years, even though classifying species within a recording could be challenging in places where acoustic diversity is high. Among the classification algorithms recently developed, BirdNET is probably the most promising. BirdNET was built to recognize over six thousand bird species and was trained using data from Xeno-canto and the Macaulay Library. Despite its huge potential, BirdNET is known to struggle with noisier recordings (1), reducing its accuracy for PAM.
publishDate 2024
dc.date.none.fl_str_mv 2024-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/257427
Barros de Araújo, Carlos; We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls; National Academy of Sciences; Proceedings of the National Academy of Sciences of The United States of America; 121; 51; 12-2024; 1-1
0027-8424
CONICET Digital
CONICET
url http://hdl.handle.net/11336/257427
identifier_str_mv Barros de Araújo, Carlos; We must not fool ourselves: A reply to Sethi et al. on the use of BirdNET to classify neotropical birdcalls; National Academy of Sciences; Proceedings of the National Academy of Sciences of The United States of America; 121; 51; 12-2024; 1-1
0027-8424
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://pnas.org/doi/10.1073/pnas.2419635121
info:eu-repo/semantics/altIdentifier/doi/10.1073/pnas.2419635121
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv National Academy of Sciences
publisher.none.fl_str_mv National Academy of Sciences
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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