卡尔曼滤波用于语音增强的一个经典代码matlab-副本.docx

卡尔曼滤波用于语音增强的一个经典代码matlab -副本function output=KalmanSignalDenoiser(Noisy,Clean,fs)

%OUTPUT=KALMANSIGNALDENOISER(NOISY,CLEAN,FS)

%this purpose of this function is to demonstrate the capability of

kalman % filter for denoising noisy speech (corrupted by white noise).

Kalman % filtering of noisy speech usually have two steps:

%1 . Estimating the AR parameters of speech segment

%2 . Filtering the segment

%There are different approaches for extracting AR parameters of

noisy % speech in the literature, however, in this function none is

implemented. % Clean speech signal should be provided for this purpose.

%

%ARGUMENTS

%NOISY : noise contaminated speech

%CLEAN : clean speech signal

%FS : Sampling frequency which should be the same for both signals

%

%Output is the denoised speech signal

%

%Required functions:

%SEGMENT

%Sep-04

%Esfandiar Zavarehei

W=fix(.025*fs); %Window length is 25 ms

SP=1; %Shift percentage is 40% (10ms) %Overlap-Add method works good with this value(.4)

SpecP=13;

Window=ones(W,1);

x=segment(Clean,W,SP,Window);

y=segment(Noisy,W,SP,Window);

n=segment(Noisy-Clean,W,SP,Window);

R=var(n);

H=[zeros(1,SpecP-1) 1];

G=H'; GGT=G*H;

FUpper=[zeros(SpecP-1,1) eye(SpecP-1)];

I=eye(SpecP);

[A Q]=lpc(x,SpecP);

P=diag(repmat(R(1),1,SpecP));

o=zeros(1,W*size(x,2));% allocating memory to the output in advance

save a lot of

computation time

o(1:SpecP)=y(1:SpecP,1)';

hwb = waitbar(0,'Please wait...','Name','Processing'); start=SpecP+1;

Sp=o(1:SpecP)';

t=SpecP+1;

for n=1:size(x,2)

waitbar(n/size(x,2),hwb,['Please wait... '

num2str(fix(100*n/size(x,2)))

' %'])

F=[FUpper; fliplr(-A(n,2:end))];

for i=start:W

S_=F*Sp;

e=y(i,n)-S_(end);%innovation

P_=F*P*F'+GGT*Q(n);

K=(P_*H')/(H*P_*H' + R(n));

SOut=S_+K*e;

o(t-SpecP+1:t)=SOut'; %Notice that the previous SpecP-1 output samples are

updated again

P=(I-K*H)*P_;

Sp=SOut;

t=t+1;

end

start=1;

end

close(hwb)

output=o;

function FormantTrack=FTrackSig(signal,fs)

%F=FTRACKSIG(S)

%Formant Tracking

% Inputs: S, signal, the speech signal with Motorola Format

and sampling

%frequency fs (default=16000 KHz)

%Outputs: F, FormantTrack is a matrix each row of which is a

track of one of

%the formants

%

%Important Variables in the program: There are several

important variables

%in the program:

%Main Function (FTrackSig)

%MaxFormantFreq : The maximum frequency of the formant % MaxBWFreq : The maximum BandWidth of the formant % SegLength: Number of samplein each frame,

%SP: Shift Percentage of frames, (1-SP is overlap percentage) % NumberOfFormants: The number of formants to be chosen % PreEmphFact:

the pre-emphasis factor

%fs: sampling frequency

%FormantCand function

%P: order of LPC model

%----------------------------------

%What does this program do:

%The speech signal is first choped into segments and the pre-

emphasize, % then windowed. Then the LPC Model for these segments are