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Inter genre similarity modeling for automatic music genre classification

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dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.kuauthorBağcı, Ulaş
dc.contributor.kuauthorErzin, Engin
dc.contributor.kuprofileMaster Student
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Computer Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid34503
dc.date.accessioned2024-11-09T23:13:36Z
dc.date.issued2013
dc.description.abstractMusic genre classification is an essential tool for music information retrieval systems and it has been finding critical applications in various media platforms. Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modelling (IGS) to improve the performance of automatic music genre classification. Inter-genre similarity information is extracted over the mis-classified feature population. Once the inter-genre similarity is modelled, elimination of the inter-genre similarity reduces the inter-genre confusion and improves the identification rates. Inter-genre similarity modelling is further improved with iterative IGS modelling(IIGS) and score modelling for IGS elimination( SMIGS). Experimental results with promising classification improvements are provided.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.identifier.doiN/A
dc.identifier.issn2413-6700
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84872736027&partnerID=40&md5=0527c4825b9a28692f0a175a92044fa7
dc.identifier.uriN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14288/10013
dc.identifier.wos245347800162
dc.keywordsClassification (of information)
dc.keywordsMusic
dc.keywordsSearch engines
dc.keywordsClassifier design
dc.keywordsCritical applications
dc.keywordsFeature classifiers
dc.keywordsFeatures extraction
dc.keywordsInformation-retrieval systems
dc.keywordsMedia platforms
dc.keywordsMusic genre classification
dc.keywordsMusic information retrieval
dc.keywordsPerformance
dc.keywordsSimilarity models
dc.keywordsInformation retrieval systems
dc.languageEnglish
dc.publisherIEEE Computer Society
dc.sourceProceedings of the International Conference on Digital Audio Effects, DAFx
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectEngineering
dc.subjectElectrical electronic engineering
dc.subjectImaging science
dc.subjectPhotographic technology
dc.titleInter genre similarity modeling for automatic music genre classification
dc.title.alternativeMüzik türlerinin sınıflandırılmasında benzer kesişim bilgileri uygulamaları
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authorid0000-0001-7379-6829
local.contributor.authorid0000-0002-2715-2368
local.contributor.kuauthorBağcı, Ulaş
local.contributor.kuauthorErzin, Engin
relation.isOrgUnitOfPublication89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae

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