《中国邮电高校学报(英文)》论文投稿模板.docx

Noisyspeechemotionrecognitionusingsamp1.ereconstructionandmu1.tip1.e-kerne1.1.earningJiangXiaoqing121XiaKcwcn1(0),1.inYong1.iang,BaiJianchuan'1. Schoo1.<X'E1.cctnx2Infixnuiitxi1.'Acrn.IfcbeiUfIiYCrtiI)MTbtKKihgy.TianjinXOU1.I.Chuu2. Schoo1.ofInZormutionScuetuxandEngiCKCnc:,UnivCnjCyfJirun.J1.n由25<K22.Cu3. InfoEXiiionCeneer.HanjinChsiian1.ivcnMy.TiCejin5(MMH4.ChinaAbstractSpeechemotionrecognition(SER)innoisyenvixmmen1.isavita1.issueinartificia1.ime1.Iigence(A1.).Inthispaper,(hereconstructionofspeechsamp1.esrcnu)vcstheaddednoise.Acousticfeaturesextractedfromthereconstructedsamp1.esarcse1.<x1.cd(obui1.danop<irna1.fe<uresubsetwithbe1.terCmO1.iona1.11xognizabih1.y.Amuhipk-keme1.(MK)support,ectormachine(SVM)c1.assifierso1.vedbyscni-dc11nitcprogramming(SDPIisadoptedinSERprocedure.TheproposedInC1.hodinthispaperisde11ms1.r<(edonBeriinDatabaseofEjnotiona1.Sptxch.Recognitionaccuraciesoftheorigina1.,noiy.andreconstructedsamp1.esc1.assifiedbybothsing1.e-kerne1.(SK)andMKc1.assifiersarccomparedandana1.yzed.Theexpcrimenia1.resu1.tsshowIhiKthepreposedIne1.hOdi、effecuveand11>bus1.whennmseexists.Kcyw<Hdxv1.Mrti<mm¾uiM,cmSeACd3fur.muK祢UcntdIf,U,IrC¼do1 IntroductionComPIenKiHiIriIyexistsbetweenhuman'sUIYeC1.iVityand1.ogica1.IhinkingkW)emotiona1.infbrma1.inissignificanttoUixkrstandtherea1.meaninginhuman'sspeech.SERisanimportantresearchfie1.dintherea1.izationofA1.11.Noiseexistingintheenvironmentandsigna1.processingsystemsinf1.uencestherecognitionaccuraciesand1.imitsthepractica1.app1.icationsofSER.suchasinte1.1.igentcustomersen*icesystemsandadjuvanttherapysystemsforautism,whereaccuraterecognitionofen)t>onsisneededtomakeaPrOperresponse.Inthispaper,noisySERisstudiedusing(hecombinationofsamp1.ereeouirUC1.ionbasedoncompressedsensing(CS)theoryandmu1.tip1.eke11>e1.1.earning(MK1.).InSER1.woessentia1.aspectsinf1.uencingthePCrfOfmansoftheemotionrecognitionsystem<reOP1.inIa1.fMUreseiandC1.YeuiWerecognitionc1.assifier.Theprecisionandinherentpropertiesofspeechfemurcsin11ectheemotiona1.rccognizabi1.ityofthefeatureset.NoisehasnegativeimpactontheextractionofacousticRoCmZX21>W2OI6C<xespriirJutk1.r：XuiKCQCr1.Emai1.:kw*i心MbinVdUeDOI:10.1016SI(K588851.17*H*features,andattcmp<s(ocopewith(henoiseinSERstartedfrom2006(2.Schu1.1.crc1.a1.SdCaedfeaturesubsetfroma4kfeaturesettorecognizecinotionsfromnoisyspeechsamp1.es3J.Youcta1.proposedenhanced1.ipschitzembeddingtoreducetheinf1.uenceofnoise4.Techniquessuchasswitching1.ineardynamicmode1.sandtwo-stageWienerfi1.teringetc.werea1.soproposedtohand1.enoisyspeechforc1.assification(5.CStheoryp11>posedbyDonohoe(a1.providespromisingmehcKtoOOiSyspeechprocessing6-7.Sparsercpfsenati>ninCStheoryhasbeenusedinnonaran>e(ricc1.assifier.Zhaoe(a1.adopted1.heenhancedsparseNPZMm1.i1.1.iOac1.assifierIode<1.with1.herx*>us1.SER.Addi1.iuna1.1.y.asIhcderivedCocffiden1.sofnisearer>sparseinanytransferd(xnain.itisimpossib1.eIor<xons(ruc1.1.henoiM:frommeasurements.Sosparsesigna1.scontaminatedbynoisecanbereconstructedwithhighqua1.ity9.Inthispaper.CStheoryisuti1.izedin(hedenoisingofnoisyspeechsamp1.esthroughsamp1.ercconstn1.ion.Acousticfeaturesofthereconstructedsamp1.esarcextractedandse1.ectedaccordingtothecomp1.ementaryinformationinOrdCrtoconstituterobustandoptima1.featuresubset.SVMisoneofthemosteffectivemethodsinpatternrecognitionprob1.ems.SVrMisakerne1.methodof11uiing(hemaximummafinhyperp1.anein(hefeatureSPaCeanditse1o11nancedependson(hekerne1.fuionstrong1.y.SoiisnecessaryIoovercome1.hekemddependCIKyindesigning1.heef1.c1.ivec1.assifierwithSVM.Inordertoirnpx>ve(heI1.cxibi1.i1.yofkerne1.fur(i>.MK1.isProPOMrdanddeveked(bina(k>nofdif1.crcntkerne1.s.1.anCkriCtcta1.PrOPOSCdMK1.withatransductionsettingfor1.earningakerne1.matrixfromdata.Themethodaimedattheop<ibinationofpredefinedbasekerne1.stogenerateagoodtargetkerne1.(1.Jincta1.Pft)POScdfeaturefusionmethodbasedonMK1.toimprovetheto<a1.SERperformanceofc1.eansamp1.es.TheWdghISofdi11crcnkerne1.scorrespondingtotheghba1.and1.oca1.featuresaregivenhughagfidSearChnh<xi(111.Inhipaper.MKfusionstrategyofHmckiietisadoptedtoimx>ve(heSVMn>de1.inabinaryInjeMructuredmuki-c1.assc1.assifier,and(hefusionCOefnCien1.qOfdifferentkerne1.sareso1.vedbyIhcSDP(ofindUPIima1.WeighISofmuI1.ip1.ckerne1.s.The3gofthep;iprarcstrc1.uredasIhcfo1.1.owings:Sect2reviews1.hebasicideaofCSinspe<xhsigna1.processingandana1.yzestheperformanceofnoisysamp1.ereconstruction.Sect.3introducesMK1.so1.vedbySDRAcousticfeaturesandfeaturese1.ectionarcpresentedinSect.4.ThCpcribrmanceeva1.uationofSERandexperimenta1.resu1.tsarci1.1.ustratedandana1.yzedinSect.5.Fina1.1.ySect.6devotestotheconc1.usions.2 CSandsamp1.ereconstructionofnoisyspeechCScombinessamp1.ingandcomssiinintooMepusingIbeminimumnumberofmeasurementsWhhmaximuminfonnation.CSaimsIurecoversparseMgna1.withfarIg(hanNyquis1.*Sh;mnonsamp1.ingr*te.u11dIbereconstructioncanbeexactunderkeyConCCPIysuch<s卬ani1.y