Linear predictive coding (LPC) of speech - Forward线性预测编码（LPC）语音了.docx

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1、SpeechProcessingProject1.inearPredictivecodingusingVoiceexcitedVocoderECE5525OsamaSarairehFall2005Dr.VetonKepuskaThebasicformofpitchexcitedLPCvocoderisshownbelowThespeechsignalisfilteredtonomorethanonehalfthesystemsamplingfrequencyandthenA/Dconversionisperformed.Thespeechisprocessedonaframebyframeba

2、siswheretheanalysisframelengthcanbevariable.Foreachframeapitchperiodestimationismadealongwithavoicingdecision.AlinearpredictivecoefficientanalysisisperformedtoobtainaninversemodelofthespeechspectrumA(z).InadditionagainparameterG,representingsomefunctionofIhespeechenergyiscomputed.Anencodingprocedure

3、isthenappliedfortransformingtheanalyzedparametersintoanefficientsetoftransmissionparameterswiththegoalofminimizingthedegradationinthesynthesizedspeechforaspecifiednumberofbits.Knowingthetransmissionframerateandthenumberofbitsusedforeachtransmissionparameters,onecancomputeanoise-freechanneltransmissi

4、onbitrate.Atthereceiver,thetransmittedparametersaredecodedintoquantizedversionsofthecoeifficentanalysisandpitchestimationparameters.Anexcitationsignalforsynthesisisthenconstructedfromthetransmittedpitchandvoicingparameters.Theexcitationsignalthendrivesasynthesisfilter1/A(z)correspondingtotheanalysis

5、modelA(z).Thedigitalsampless(n)arethenpassedthroughanD/Aconverterandlowpassfilteredtogeneratethesyntheticspeechs(t).Eitherbeforeoraftersynthesis,thegainisusedtomatchthesyntheticspeechenergytotheactualspeechenergy.Thedigitalsamplesaretheconvertedtoananalogsignalandpassedthroughafiltersimilartotheonea

6、ttheinputofthesystem.LMearDrediCtiVeCOdin父(LPC)OfSDeeChThelinearpredictivecoding(LPC)methodforspeechanalysisandsynthesisisbasedonmodelingtheVocaltractasalinearAll-Pole(IIR)filterhavingthesystemtransferfunction:T = pitd periodimpulse trainInnovationsu(n)。UVSpeech SignalLPC FilterWI)whitenoisesimplesp

7、eechproductionWherepisthenumberofpoles,GisthefilterGain,andakaretheparametersthatdeterminethepoles.Therearetwomutuallyexclusivewaysexcitationfunctionstomodelvoicedandunvoicedspeechsounds.Forashorttime-basisanalysis,voicedspeechisconsideredperiodicwithafundamentalfrequencyofFo,andapitchperiodoflFo,wh

8、ichdependsonthespeaker.Hence,Voicedspeechisgeneratedbyexcitingtheallpolefiltermodelbyaperiodicimpulsetrain.Ontheotherhand,unvoicedsoundsaregeneratedbyexcitingtheall-polefilterbytheoutputofarandomnoisegenerator.Thefundamentaldifferencebetweenthesetwotypesofspeechsoundscomesfromthewaytheyareproduced.T

9、hevibrationsofthevocalcordsproducevoicedsounds.Therateatwhichthevocalcordsvibratedictatesthepitchofthesound.Ontheotherhand,unvoicedsoundsdonotrelyonthevibrationofthevocalcords.Theunvoicedsoundsarecreatedbytheconstrictionofthevocaltract.Thevocalcordsremainopenandtheconstrictionsofthevocaltractforceai

10、routtoproducetheunvoicedsoundsGivenashortsegmentofaspeechsignal,letssayabout20msor160samplesatasamplingrate8KHz,thespeechencoderatthetransmittermustdeterminetheproperexcitationfunction,thepitchperiodforvoicedspeech,thegain,andthecoefficients3pk.Theblockdiagrambelowdescribestheencoder/decoderfortheLi

11、nearPredictiveCoding.Theparametersofthemodelaredeterminedadaptivelyfromthedataandmodeledintoabinarysequenceandtransmittedtothereceiver.Atthereceiverpoint,thespeechsignalisthesynthesizedfromthemodelandexcitationsignal.Theparametersoftheall-polefiltermodelaredeterminedfromthespeechsamplesbymeansofline

12、arprediction.TobespecifictheoutputofIheLinearPredictionfilterisPS()=工ap(k)s(nk)k=landthecorrespondingerrorbetweentheobservedsampleS(n)andthepredictedvalueAs(h)ise(h)=s(ri)一s(h)byminimizingthesumofthesquarederrorwecandeterminethepoleparameters/7(Jofthemodel.Theresultofdifferentiatingthesumabovewithre

13、specttoeachoftheparametersandequationtheresulttozero,isasepofplinearequationsP%(Z)Q(机幻=_噎(MWherem=I2.pk=whereGS(Mpresenttheautocorrelationofthesequence$()definedasNQ(M=s()s5+m)H=OtheequationabovecanbeexpressedinmatrixformasRd=一曝whereRSSaisapxpautocorrelationmatrix,GsiSaPXlautocorrelationvector,andai

14、sapx1vectorofmodelparameters.rowcol=size(data);ifcol=1data=data;endnfrane=0;msfr=round(srl(X)Ofr);%Convertmstosamplesmsfs=round(sr/1000*fs);%Convertmstosamplesduration=Iength(data);speech=filler01-preemp,1,data);%Preemphasizespeechnsoverlap=msfs-nsfr;ramp=0:1/(nsoverlap-1):1J;%Computepartofwindowfor

15、frameindex=1:msfr:duration-msfs+1%framerate=20rnsframeData=speech(frameindex:(frameIndex+ms-1);%framesize=3Omsnframe=nfrane+l;CiiitoCor=XcorriframeData);%ComputethecrosscorrelationautoCorVec=autoCor(msfs+0:LJ);TheseequationscanbesolvedinMATLBbyusingtheLevinson-Durbinalgorithm.%Levinsonsmethoderr(1)=

16、autoCorVec(I);k(l)=O;=;farindex=1:Lnumerator=/7A.*autoCorVec(index+1:-1:2);denominator=-1*err(index);k(index)=nuneratordenoninator;%PARCORcoeffsA=A+k(index)*flipud（八）;k(index)J;err(index+l)=(1-k(index)2)*err(index);Thegainparameterofthefiltercanbeobtainedbytheinput-outputrelationshipasfollowPs(n)=-Za