Within class optimization of cepstra for speaker recognition
J. Thompson, J. S. Mason · 1993
WITHINCLASSOPTIMIZATIONOFCEPSTRAFORSPEAKERRECOGNITIONJ.Thompson&J.S.MasonDepartmentofElectrical&ElectronicEngineering,UniversityCollegeofSwansea,SWANSEA,SA28PP,UKABSTRACTByidentifyinghighlysp eakersp eci casp ectsofcep-stralfeatures,thetaskofsp eakerrecognitioncanb ep otentiallysimpli ed.Theidenti cationpro cesscanb ep erformedb othphoneticallyandinthecepstraldomain.Thephoneticanalysisaimstodeterminethetemp oralasp ectsofutteranceswhichexhibitthehighestdegreeofsp eakersp eci city,whilecepstralanalysisexaminesindividualcepstrawithinthesetemp oraldivisions.Thispap eraimstocom-plementworkthathasalreadyb eenconductedonaphoneticbasis,byp erforminganalysisup onthein-dividualcepstralco ecientswithinutterances.Keywords:Sp eakerRecognition,Sp eci- city,Inter-sp eakerVariation,tra-sp eakaria-tion.1INTRODUCTIONInvestigationsintothephoneticasp ectsofsp eechsp eakerrecognitionarerep ortedbyEato ck[1 ],vandenHeuvel[2 ]andBonastre[3].Intheseinvestiga-tions,ithasb eenfoundthatsp eakersp eci cityvariesnoticeablyb etweendi erentphoneticsubgroups,butremainsmoreconstantwithinthem.Thesephonemesubgroupscanb ecrudelyrankedinthefollowingor-der:longvowels,nasals,shortfricatives,andplosives,wherelongvowelsexhibitthehighestdegreeofsp eakersp eci city,andplosivesthelowest.Thispap erexaminesthecepstralrepresentationsofutterances,inparticularthosesubgroupswhichex-hibitahighsp eakersp eci citysuchaslongvowelsandnasals.Moresp eci callytheaimistoidentifyindividualcepstralco ecientswhichcontainthema-jorityofthesp eakersp eci cinformation,andshowbyanalysisofcepstraldistributions,whsomesp eak-ersp erformsigni cantlyworsethanothers.Severalb ene tsfromidentifyingthemoste ectiveco ecientsexist.Firstlytherecognitionsystemcanb ereducedincomplexitybusingcepstrathatcon-tainahighdegreeofsp eakersp eci city.Secondly,p erhapsb etteroverallp erformancecanb eachievedby`liftering'thefeaturevectorspriortoclassi ca-tion[4],wherethecepstraweightingsarederiveddi-rectlyfromtheaverageoftheirsp eakersp eci cityforagroupofsp eakers.Exp erimentssimilarnaturearerep ortedonfrequencydomainfeaturesusingavariancemeasure[5 ]andmultiplefeaturesusingdy-namicprogramming[6 ][7].2CEPSTRALFEATURESThecepstralfeaturesconsideredherearegeneratedfromasp eechdatabaseusing24channelDFT-simulatedmel lter-bank[8 ],witha95%overlapb e-tweensuccessiveframes.This lterbankiswidelyusedandleadstothestandardformofmelcepstra.Thesp eechdatabaseconsistsof20sp eakers(10male,10female),utteringthelettersofalphab et(atoz)threetimes.Thesamplingrateofthedatais10KHz.Ofthe24p ossiblestandardcepstralfeaturesonlyMFCCs1-14areusedinordertoremovethema jor-ityofpitchinformation(whicmaexhibitamis-leadinglyhighsp eakersp eci citybutisprobablyanunreliableparameterinpracticalsp eakerrecognitionsystems[9 ]).Alsothisreduceddimensionfeaturesetisinverseariance,zeromeanweighted,onaglobalp o oledbasis.