Problem in calling multiple reurns and counting number of args passed

Hiii...

i.m in mid of my program.... as the following code is in MATLAB and i'm converting these into JAVA.... but there i stuck with an strange problems wiz..

1) i can't call multiple returns for multiple variable declaration in different method... and...

2) how can i count the number of arguments passed in an method...

Problems in following piece of code:

function [NoiseFlag, SpeechFlag, NoiseCounter, Dist]=vad(signal,noise,NoiseCounter,NoiseMargin,Hangover)

%[NOISEFLAG, SPEECHFLAG, NOISECOUNTER, DIST]=vad(SIGNAL,NOISE,NOISECOUNTER,NOISEMARGIN,HANGOVER)

%Spectral Distance Voice Activity Detector

%SIGNAL is the the current frames magnitude spectrum which is to labeld as

%noise or speech, NOISE is noise magnitude spectrum template (estimation),

%NOISECOUNTER is the number of imediate previous noise frames, NOISEMARGIN

%(default 3)is the spectral distance threshold. HANGOVER ( default 8 )is

%the number of noise segments after which the SPEECHFLAG is reset (goes to

%zero). NOISEFLAG is set to one if the the segment is labeld as noise

%NOISECOUNTER returns the number of previous noise segments, this value is

%reset (to zero) whenever a speech segment is detected. DIST is the

%spectral distance.

%Saeed Vaseghi

%edited by Esfandiar Zavarehei

%Sep-04

if nargin<4

NoiseMargin=3;

end

if nargin<5

Hangover=8;

end

if nargin<3

NoiseCounter=0;

end

FreqResol=length(signal);

SpectralDist= 20*(log10(signal)-log10(noise));

SpectralDist(find(SpectralDist<0))=0;

Dist=mean(SpectralDist);

if (Dist < NoiseMargin)

NoiseFlag=1;

NoiseCounter=NoiseCounter+1;

else

NoiseFlag=0;

NoiseCounter=0;

end

% Detect noise only periods and attenuate the signal

if (NoiseCounter > Hangover)

SpeechFlag=0;

else

SpeechFlag=1;

end

Main MATLAB Program :

function output=MultibandSS(signal,fs)

% OUTPUT=SSMULTIBAND(S,FS,IS)

% Multi-band Spectral subtraction

% subtraction with adjusting subtraction factor. the adjustment is

% according to local a postriori SNR and the frequency band.

% 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)

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=2;%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

NoiseCounter=0;

NoiseLength=25;%This is a smoothing factor for the noise updating

Beta=.03;

minalpha=1;

maxalpha=5;

minSNR=-5;

maxSNR=20;

alphaSlope=(minalpha-maxalpha)/(maxSNR-minSNR);

alphaShift=maxalpha-alphaSlope*minSNR;

BN=Beta*N;

%Delta is a frequency dependent coefficient

Delta=1.5*ones(size(BN));

Delta(1:fix((-2000+fs/2)*FreqResol*2/fs))=2.5; %if the frequency is lower than FS/2 - 2KHz

Delta(1:fix(1000*FreqResol*2/fs))=1; %if the frequency is lower than 1KHz

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

BN=Beta*N;

end

SNR=10*log(Y(:,i)./N);

alpha=alphaSlope*SNR+alphaShift;

alpha=max(min(alpha,maxalpha),minalpha);

D=Y(:,i)-(Delta.*alpha.*N); %Nonlinear (Non-uniform) Power Specrum Subtraction

X(:,i)=max(D,BN); %if BY>D X=BY else X=D which sets very small values of subtraction result to an attenuated

%version of the input power spectrum.

end

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

function ReconstructedSignal=OverlapAdd2(XNEW,yphase,windowLen,ShiftLen);

%Y=OverlapAdd(X,A,W,S);

%Y is the signal reconstructed signal from its spectrogram. X is a matrix

%with each column being the fft of a segment of signal. A is the phase

%angle of the spectrum which should have the same dimension as X. if it is

%not given the phase angle of X is used which in the case of real values is

%zero (assuming that its the magnitude). W is the window length of time

%domain segments if not given the length is assumed to be twice as long as

%fft window length. S is the shift length of the segmentation process ( for

%example in the case of non overlapping signals it is equal to W and in the

%case of %50 overlap is equal to W/2. if not givven W/2 is used. Y is the

%reconstructed time domain signal.

%Sep-04

%Esfandiar Zavarehei

if nargin<2

yphase=angle(XNEW);

end

if nargin<3

windowLen=size(XNEW,1)*2;

end

if nargin<4

ShiftLen=windowLen/2;

end

if fix(ShiftLen)~=ShiftLen

ShiftLen=fix(ShiftLen);

disp('The shift length have to be an integer as it is the number of samples.')

disp(['shift length is fixed to ' num2str(ShiftLen)])

end

[FreqRes FrameNum]=size(XNEW);

Spec=XNEW.*exp(j*yphase);

if mod(windowLen,2) %if FreqResol is odd

Spec=[Spec;flipud(conj(Spec(2:end,:)))];

else

Spec=[Spec;flipud(conj(Spec(2:end-1,:)))];

end

sig=zeros((FrameNum-1)*ShiftLen+windowLen,1);

weight=sig;

for i=1:FrameNum

start=(i-1)*ShiftLen+1;

spec=Spec(:,i);

sig(start:start+windowLen-1)=sig(start:start+windowLen-1)+real(ifft(spec,windowLen));

end

ReconstructedSignal=sig;