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1、MultimedToolsAppl(2012)58:521–541DOI10.1007/s11042-011-0729-xAcross-modalmethodoflabelingmusictagsJia-LienHsu·Yen-FuLiPublishedonline:26January2011©SpringerScience+BusinessMedia,LLC2011AbstractInthispaper,wediscussvariousfeaturesofmusicobjectsintwokindsofdomain.Amongthesefeatures,Mel-frequ
2、encycepstralcoefficients(MFCCs)arefurtherdiscussedanddescribedbyGaussianmixturemodel(GMM).Also,thesimilaritybetweenGMMsareinvestigatedaccordingly.Then,weemploythemulti-mediagraphasacross-modalmethodtoassociateMFCCsandgenretagsofmusicobjects.Byapplyinglinkanalysisalgorithminthegraph,welabel
3、appropriategenretagsfortargetmusicobjects.Also,weperformexperimentstoshowperformance,effectiveness,andparametersettingofourapproach.KeywordsCross-modal·Mel-frequencycepstralcoefficients(MFCCs)·Gaussianmixturemodel(GMM)·Taglabeling·Musicinformationretrieval1IntroductionInthemusicinformation
4、retrieval(MIR)system,thefeatureextractionisstilloneofthekeyissues.Amusicobjectcontainsmulti-facetfeaturesinvariousfeaturedomains,suchasMel-frequencycepstralcoefficients(MFCCs),frequency,speed,timbre,melody,rhythm,andgenre.Usingsignalprocessingtechniques,somespecificmusicmetadatacanbeextrac
5、tedfromaudiosignalofmusicobjects.However,somemusiccontentdescriptorsandfeaturesareparticularlychallengingtobeextracted,e.g.,musicgenretags,whichcannotbeeasilyderivedbyonlyapplyingcomputationalmethodsonaudiosignalofmusicobjects.ThisresearchwassupportedbyFuJenCatholicUniversitywithProjectNo.
6、409731044039,andsponsoredbytheNationalScienceCouncilunderContractNo.NSC-97-2221-E-030-013.J.-L.Hsu(B)·Y.-F.LiDepartmentofComputerScienceandInformationEngineering,FuJenCatholicUniversity,Taiwan,RepublicofChinae-mail:alien@csie.fju.edu.tw522MultimedToolsAppl(2012)58:521–541Whendealingwithmus
7、icobjects,weconcludethatthesefeaturesareseparatedintotwokindsofdomaintypes,i.e.,quantifiedandunquantifiablefeaturedomain,showninFig.1.Inthequantifiedfeaturedomain,mostfeaturesarerepresentedasnumericalvalues.Forexample,theaveragefrequencyofmusicobjectis80Hz.Ont
