fbana4.m

来自「这是一个用于语音信号处理的工具箱」· M 代码 · 共 321 行

% Function: perform fourth stage of the Formant Based Linear Prediction Analysis
%           ==> encode the source characteristics

function [gm,gpcof,ncidx,ncgm]=fbana4(signal,basic,nframe,Froot,gci,voicetype,cofa);


%retrieve the basic specification
F_len=basic(5);
O_lap=basic(6); 
Order=basic(4);
M_len=F_len-O_lap;

%%-------------------%%
%% inverse filtering %%
%%-------------------%%

froot=zeros(10,1);
kf=1;
froot=Froot(kf,:)';
fmpoly=real(poly(froot));
order=length(fmpoly)-1;

%****** frequency lifting ******%
%cofa1=cofa(kf,:);
%fmpoly=ad_lpc1(cofa1,fmpoly);

coffa(kf,:)=fmpoly;

sso=signal( (kf-1)*M_len+1:kf*M_len+order+O_lap );
dgf1=filter(fmpoly, 1, sso);
dgf1(1:order)=[];
sso(1:10)=[];

% Normalize the gain
eng=sso*sso';
eng1=dgf1*dgf1';
dgf1=sqrt(eng/eng1)*dgf1;

dgf( (kf-1)*M_len+order+1:kf*M_len+O_lap+order)=dgf1;
dgf2=dgf1(M_len+1:F_len);

for kf=2:nframe-1
   froot=Froot(kf,:)';
   fmpoly=real(poly(froot));
   order=length(fmpoly)-1;
   
   %******* frequency lifting ******%
   %cofa1=cofa(kf,:);
   %fmpoly=ad_lpc1(cofa1,fmpoly);
   
   coffa(kf,:)=fmpoly;
   
   % inverse filtering
   sso=signal( (kf-1)*M_len+1:kf*M_len+O_lap+order );
   dgf1=filter(fmpoly, 1, sso);
   dgf1(1:order)=[];
   sso(1:10)=[];
   
   % Normalize the gain
   eng=sso*sso';
   eng1=dgf1*dgf1';
   dgf1=sqrt(eng/eng1)*dgf1;
   
   % overlap region
   dgfo=( dgf2.*(O_lap:-1:1)+dgf1(1:O_lap).*(1:O_lap) )/(O_lap+1); 
   dgf((kf-1)*M_len+order+1:kf*M_len+O_lap+order)=[dgfo dgf1(O_lap+1:F_len)];
   dgf2=dgf1(M_len+1:F_len);
end

%disp('Inverse filtering is complete!');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%                           %%%%%%
%%%%%%%  Find glottal coefficient %%%%%%
%%%%%%%  6-order polynomial model %%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% This step will create the following variables :
%
%	gpcof = glottal codeword for each pitch period.
 
%-----------------------------%
% construct the ploc1 matrix  %
%-----------------------------%

ploc1=zeros(nframe,10);
k_back=0;
for i=1:length(gci)
   k=fix( (gci(i)-Order)/M_len +1);
   aa=gci(i)-Order-(k-1)*M_len;
   if aa==0 
      k=k-1;
      aa=M_len;
   end
   if (k-k_back)==0
      idx=idx+1;
   else
      idx=1;
   end  

   ploc1(k,idx)=aa;
   k_back=k;
end

gpcof=zeros(nframe,7);
gm=zeros(nframe,10);

dgf=filter([1 1],[1 0.98],dgf); % remove high-frequency noise 
%dgf=integ(dgf);  % integrate the differential glottal flow in a whole 
%gf=filtfilt([1 -1],[1 -0.99],dgf); % gf== glottal flow

%***** Select Glottal Source model
%***** Smodel==1 --> 6 order polynomial model  sounds better ******%
%***** Smodel==2 --> LF model                                ******%

Smodel=basic(3);

for kf=2:nframe-1
   if ploc1(kf,1)
      startp=M_len*(kf-1)+Order;
      self=ploc1(kf,:);
      self=self(self~=0);
      if ploc1(kf+1,1)
         after=ploc1(kf+1,1)+M_len;
      elseif voicetype(kf+1) & kf <= nframe-2 
         if ploc1(kf+2,1)
            after=ploc1(kf+2,1)+2*M_len;
         else
            after=[];
         end;
      else
         after=[];
      end;
      period=[self after]+startp;
      lenp=length(period);
      if lenp>1
         gcof=[];
         for k=1:lenp-1
            
            seggp=dgf(period(k):period(k+1));
            seggp=seggp-mean(seggp);
            
            % Polynomial model when Smodel==1 ***
            if Smodel==1
               gcof(k,:)=polym1( seggp );
               %  poly1 <--> gen_dgf1
               
               % LF model when Smodel==2 ***
            elseif Smodel==2
               seggp=integ(seggp);
               [Rd,Ee]=lfmodel(seggp);
               Ra=(-1+4.8*Rd)/100;
               Rk=(22.4+11.8*Rd)/100;
               Rg=Rk/4/( 0.11*Rd/(0.5+1.2*Rk)-Ra);
               T0=length(seggp)-1;
               Ta=T0*Ra;
               Tp=T0/2/Rg;
               Te=floor(Tp*Rk+Tp);
               Tc=T0;
               gcof(k,1:7)=[Tp/T0 Te/T0 Ta/T0 Tc/T0 Ee 0 0];
            end
         end;
         if lenp<=2
            avegcof=gcof;
         else
            avegcof=mean(gcof);
         end;
         gpcof(kf,:)=avegcof;
         
      end % if lenp>1
   end;
end;
gcof=[];

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%                                     %%
%%%%%%%  energy encoding for voiced speech  %%
%%%%%%%                                     %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% This step will create the following variables :
%
%	gm = signal power for each pitch period.

% encoding the energy for pitch period
numgci=length(gci);
gm=zeros(1,numgci);
if numgci>1
   lenss=gci(2)-gci(1);
end
for nk=1:numgci
   
   startp=gci(nk)+1;  % starting point of the pitch period
   kf=fix( (startp-Order-1)/M_len )+1; % frame number
   
   % the last gci
   if nk==numgci
      endp=startp+lenss-1;
   else
      endp=gci(nk+1);  % ending point of the pitch period
      olens=lenss;
      lenss=gci(nk+1)-gci(nk);
   end
   
   % voiced-to-unvoiced transition
   if lenss>F_len
      if voicetype(kf)==1 & voicetype(kf+1)==0
         lenss=olens;
         endp=startp+lenss-1;
      end
   end
   
   sp=signal(startp:endp);
   gm(nk)=(sp*sp')/lenss;
end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%                                        %%
%%%%%%%  energy encoding for the whole speech  %%
%%%%%%%                                        %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% This step will create the following variables :
%
%    ncgm = signal power for Xlen period; size(ncgm)=[nframe,4]

ncgm=zeros(nframe,4);
Xlen=M_len/4;
for kf=1:nframe
   for kk=1:4
      startp=(kf-1)*M_len+Order+(kk-1)*Xlen+1;
      ss1=signal(startp:startp+Xlen-1);
      ncgm(kf,kk)=(ss1*ss1')/Xlen;
   end
end

%disp('Glottal codeword searching is completed!'); toc;
%disp('');
%disp('It takes a while to perform codeword searching for unvoiced speech.');
%disp('Please wait! Please wait! Please wai--------------------------------t.');
%disp('');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%                            %%
%%%%%%%  Find unvoiced codeword    %%
%%%%%%%                            %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% This step will create the following variable :
%
%	ncidx = glottal codeword.

% Function : preprocess before performing codeword searching.  This includes
%		1. removal of filter memory contribution,
%		2. spectral weighting.

load nc;  % Load the stochastic codebook
Xlen=M_len/4;
Ziy1=zeros(1,Order);  % Reset filter memory at the beginning
for kf=1:nframe
   if kf==1 | kf==nframe
      proc='nc';
   elseif sum(voicetype(kf-1:kf))<2 | sum(voicetype(kf:kf+1))<2
		proc='nc';
   else
      proc='mp';
   end;
   if proc=='nc'  % Proceed if it is an unvoiced segment
      ocofa=cofa(kf,:);
      ncofa=ocofa.*((0.8).^(0:length(ocofa)-1));
      if kf>1
         if voicetype(kf-1)
			Ziy1=signal((kf-1)*M_len+Order:-1:(kf-1)*M_len+1);
         % Note : filter memory is regarded as the past samples
			% for the Direct-I implementation
      end;
   end;
   if kf==1 
      so=signal((kf-1)*M_len+Order+1:kf*M_len+Order);
   else
      so=signal((kf-1)*M_len+Order+1:kf*M_len+Order)-...
         filt(1,ocofa,zeros(1,M_len),Ziy1);
      % Remove filter memory carried over from the previous frame
   end
   ss=filter(ocofa,ncofa,so);  % spectral weighting 
   % PURPOSE: De-emphasize errors at the formant regions
   noise1=[];
   Ziy=Ziy1;  % filter memory
   
   for kk=1:4
      cmp1=ss(1+(kk-1)*Xlen:Xlen*kk);
      sub1=filt(1,ncofa,zeros(1,Xlen),Ziy);
      cmp=cmp1-sub1;  % eliminate memory contribution
      ncidx(kf,kk)=fdncb0(cmp,ncofa,nc0,Rnc0);
      
      % track the filter memory
      eng1=ncgm(kf,kk);
      noise=nc0(ncidx(kf,kk),:);
      if Xlen~=50
         noise=interpft(noise,Xlen);
      end
      ss2=filt(1,ocofa,noise,Ziy);
      eng2=sum(ss2.^2);
      amp=sqrt(eng1/eng2);

		% Concatenate the excitation in every subframe as a whole
		noise1=[noise1 amp*noise];
      nsyn=amp*ss2;
		Ziy=nsyn(Xlen:-1:Xlen-Order+1);
   end
   ss1=filt(1,ocofa,noise1,Ziy1);
   Ziy1=ss1(M_len:-1:M_len-Order+1);  % Track the filter memory
end	
end

clear Rnc0 nc0 ss1 ss2 noise noise1;

%disp('Stochastic codeword searching is completed!'); toc;
%disp('');
%disp('Analysis is OK! You may perform speech synthesis now!');