Automated Bioacoustic Monitoring for South African Bird Species on Unlabeled Data

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dc.contributor.authorDoell, Michael
dc.contributor.authorKuehn, Dominik
dc.contributor.authorSuessle, Vanessa
dc.contributor.authorBurnett, Matthew J.
dc.contributor.authorDowns, Colleen T.
dc.contributor.authorWeinmann, Andreas
dc.contributor.authorHergenroether, Elke
dc.contributor.editorSkala, Václav
dc.date.accessioned2024-07-27T17:53:48Z
dc.date.available2024-07-27T17:53:48Z
dc.date.issued2024
dc.description.abstract-translatedAnalyses for biodiversity monitoring based on passive acoustic monitoring (PAM) recordings is time-consuming and chal lenged by the presence of background noise in recordings. Existing models for sound event detection (SED) worked only on certain avian species and the development of further models required labeled data. The developed framework automatically extracted labeled data from available platforms for selected avian species. The labeled data were embedded into recordings, including environmental sounds and noise, and were used to train convolutional recurrent neural network (CRNN) models. The models were evaluated on unprocessed real world data recorded in urban KwaZulu-Natal habitats. The Adapted SED-CRNN model reached a F1 score of 0.73, demonstrating its efficiency under noisy, real-world conditions. The proposed approach to automatically extract labeled data for chosen avian species enables an easy adaption of PAM to other species and habitats for future conservation projects.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationWSCG 2024: full papers proceedings: 32. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 23-32.en
dc.identifier.doihttps://doi.org/10.24132/CSRN.3401.4
dc.identifier.issn2464–4625 (online)
dc.identifier.issn2464–4617 (print)
dc.identifier.urihttp://hdl.handle.net/11025/57381
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.rights© Václav Skala - UNION Agencyen
dc.rights.accessopenAccessen
dc.subjectbioakustické monitorovánícs
dc.subjectdruhová klasifikacecs
dc.subjectspektrogramycs
dc.subjectkonvoluční rekurentní neuronová síťcs
dc.subjectobousměrná GRUcs
dc.subjectekologiecs
dc.subjectzachování divoké zvěřecs
dc.subject.translatedbioacoustic monitoringen
dc.subject.translatedspecies classificationen
dc.subject.translatedspectrogramsen
dc.subject.translatedCNNsen
dc.subject.translatedconvolutional recurrent neural networken
dc.subject.translatedbidirectional GRUen
dc.subject.translatedecologyen
dc.subject.translatedwildlife conservationen
dc.titleAutomated Bioacoustic Monitoring for South African Bird Species on Unlabeled Dataen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer revieweden
dc.type.versionpublishedVersionen

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