ssboll79.m

提供了集中语音去噪的matlab代码

function output=SSBoll79(signal,fs,IS)

% OUTPUT=SSBOLL79(S,FS,IS)
% Spectral Subtraction based on Boll 79. Amplitude spectral subtraction 
% Includes Magnitude Averaging and Residual noise Reduction
% S is the noisy signal, FS is the sampling frequency and IS is the initial
% silence (noise only) length in seconds (default value is .25 sec)
%
% April-05
% Esfandiar Zavarehei

if (nargin<3 | isstruct(IS))
    IS=.25; %seconds
end
W=fix(.025*fs); %Window length is 25 ms
nfft=W;
SP=.4; %Shift percentage is 40% (10ms) %Overlap-Add method works good with this value(.4)
wnd=hamming(W);

% IGNORE THIS SECTION FOR CAMPATIBALITY WITH ANOTHER PROGRAM FROM HERE.....
if (nargin>=3 & isstruct(IS))%This option is for compatibility with another programme
    W=IS.windowsize
    SP=IS.shiftsize/W;
    nfft=IS.nfft;
    wnd=IS.window;
    if isfield(IS,'IS')
        IS=IS.IS;
    else
        IS=.25;
    end
end
% .......IGNORE THIS SECTION FOR CAMPATIBALITY WITH ANOTHER PROGRAM T0 HERE

NIS=fix((IS*fs-W)/(SP*W) +1);%number of initial silence segments
Gamma=1;%Magnitude Power (1 for magnitude spectral subtraction 2 for power spectrum subtraction)

y=segment(signal,W,SP,wnd);
Y=fft(y,nfft);
YPhase=angle(Y(1:fix(end/2)+1,:)); %Noisy Speech Phase
Y=abs(Y(1:fix(end/2)+1,:)).^Gamma;%Specrogram
numberOfFrames=size(Y,2);
FreqResol=size(Y,1);

N=mean(Y(:,1:NIS)')'; %initial Noise Power Spectrum mean
NRM=zeros(size(N));% Noise Residual Maximum (Initialization)
NoiseCounter=0;
NoiseLength=9;%This is a smoothing factor for the noise updating

Beta=.03;

YS=Y; %Y Magnitude Averaged
for i=2:(numberOfFrames-1)
    YS(:,i)=(Y(:,i-1)+Y(:,i)+Y(:,i+1))/3;
end

for i=1:numberOfFrames
    [NoiseFlag, SpeechFlag, NoiseCounter, Dist]=vad(Y(:,i).^(1/Gamma),N.^(1/Gamma),NoiseCounter); %Magnitude Spectrum Distance VAD
    if SpeechFlag==0
        N=(NoiseLength*N+Y(:,i))/(NoiseLength+1); %Update and smooth noise
        NRM=max(NRM,YS(:,i)-N);%Update Maximum Noise Residue
        X(:,i)=Beta*Y(:,i);
    else
        D=YS(:,i)-N; % Specral Subtraction
        if i>1 && i<numberOfFrames %Residual Noise Reduction            
            for j=1:length(D)
                if D(j)<NRM(j)
                    D(j)=min([D(j) YS(j,i-1)-N(j) YS(j,i+1)-N(j)]);
                end
            end
        end
        X(:,i)=max(D,0);
    end
end

output=OverlapAdd2(X.^(1/Gamma),YPhase,W,SP*W);