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Speeh/Music classification by using statistical neural networks

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dc.contributor.authorBolat, B
dc.contributor.authorKüçük, Ü
dc.date.accessioned2026-06-27T12:56:37Z
dc.date.issued2004
dc.description.abstractThis paper represents a framework for speech/music classification by using statistical neural networks. Zero Crossing Rate, Root Mean Square Power and Spectral Centroid were used as features. A dataset include 150 audio instances were labeled manually and 105 of them were used to train different networks which are PNN, GRNN and RBF. The remaining of the dataset were used as test item. Training and test performances of these three network types were discussed.en
dc.description.urihttps://doi.org/10.1109/siu.2004.1338300
dc.identifier.doi10.1109/siu.2004.1338300
dc.identifier.endpage229
dc.identifier.isbn0-7803-8318-4
dc.identifier.startpage227
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47967
dc.identifier.wos000225861200058
dc.language.isotur
dc.publisherIEEE
dc.relation.conferenceIEEE 12th Signal Processing and Communications Applications Conference
dc.relation.ispartofPROCEEDINGS OF THE IEEE 12TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleSpeeh/Music classification by using statistical neural networks
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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