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Music Genre Classification and Recommendation by Using Machine Learning Techniques

dc.contributor.authorElbir, Ahmet
dc.contributor.authorCam, Hilmi Bilal
dc.contributor.authorIyican, Mehmet Emre
dc.contributor.authorOzturk, Berkay
dc.contributor.authorAydin, Nizamettin
dc.date.accessioned2026-06-27T14:20:20Z
dc.date.issued2018
dc.description.abstractMusic genre prediction is one of the topics that digital music processing is interested in. In this study, acoustic features of music have been extracted by using digital signal processing techniques and then music genre classification and music recommendations have been made by using machine learning methods. In addition, convolutional neural networks, which are deep learning methods, were used for genre classification and music recommendation and performance comparison of the obtained results has been. In the study, GTZAN database has been used and the highest success was obtained with the SVM algorithm.en
dc.identifier.endpage139
dc.identifier.isbn978-1-5386-7786-5
dc.identifier.startpage135
dc.identifier.urihttps://hdl.handle.net/20.500.14981/59434
dc.identifier.wos000455592800018
dc.language.isoeng
dc.publisherIEEE
dc.relation.conferenceInnovations in Intelligent Systems and Applications Conference (ASYU)
dc.relation.ispartof2018 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU)
dc.subjectMusic genre Classification
dc.subjectAcoustic features
dc.subjectMachine Learning
dc.subjectDeep Learning
dc.subjectFEATURES
dc.subjectComputer Science
dc.subjectEngineering
dc.titleMusic Genre Classification and Recommendation by Using Machine Learning Techniques
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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