Animal sound classification using a convolutional neural network

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dc.authorid0000-0002-8649-6013
dc.contributor.authorŞaşmaz, Emreen_US
dc.contributor.authorTek, Faik Borayen_US
dc.date.accessioned2019-03-16T21:58:05Z
dc.date.available2019-03-16T21:58:05Z
dc.date.issued2018-12-06
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.description.abstractIn this paper, we investigate the problem of animal sound classification using deep learning and propose a system based on convolutional neural network architecture. As the input to the network, sound files were preprocessed to extract Mel Frequency Cepstral Coefficients (MFCC) using LibROSA library. To train and test the system we have collected 875 animal sound samples from an online sound source site for 10 different animal types. We report classification confusion matrices and the results obtained by different gradient descent optimizers. The best accuracy of 75% was obtained by Nesterov-accelerated Adaptive Moment Estimation (Nadam).en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationŞaşmaz, E. & Tek, F. B. (2018). Animal sound classification using A convolutional neural network. Paper presented at the 2018 3rd International Conference on Computer Science and Engineering (UBMK), 625-629. doi:10.1109/UBMK.2018.8566449en_US
dc.identifier.doi10.1109/UBMK.2018.8566449
dc.identifier.endpage629
dc.identifier.isbn9781538678930
dc.identifier.isbn9781538678923
dc.identifier.isbn9781538678947
dc.identifier.scopus2-s2.0-85060595306
dc.identifier.scopusqualityN/A
dc.identifier.startpage625
dc.identifier.urihttps://hdl.handle.net/11729/1453
dc.identifier.urihttp://dx.doi.org/10.1109/UBMK.2018.8566449
dc.identifier.wosWOS:000459847400120
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.institutionauthorŞaşmaz, Emreen_US
dc.institutionauthorTek, Faik Borayen_US
dc.institutionauthorid0000-0002-8649-6013
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 3rd International Conference on Computer Science and Engineering (UBMK)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAnimal sound classificationen_US
dc.subjectMel frequency cepstral coefficient (MFCC)en_US
dc.subjectConvolution neural network (CNN)en_US
dc.subjectConfusion matrix (CF)en_US
dc.subjectBirdsen_US
dc.subjectAcousticsen_US
dc.subjectAcoustic indicesen_US
dc.subjectConvolutionen_US
dc.subjectDeep learningen_US
dc.subjectImage resolutionen_US
dc.subjectNetwork architectureen_US
dc.subjectNeural networksen_US
dc.subjectAnimal typesen_US
dc.subjectConfusion matricesen_US
dc.subjectConvolution neural networken_US
dc.subjectConvolutional neural networken_US
dc.subjectGradient descenten_US
dc.subjectMel-frequency cepstral coefficientsen_US
dc.subjectMoment estimationen_US
dc.subjectSound classificationen_US
dc.subjectAnimalsen_US
dc.titleAnimal sound classification using a convolutional neural networken_US
dc.typeConference Objecten_US

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