Speech endpoint detection on multiple wave signal.

Hi all, I have two function of MATLAB .The first function is to do the endpoint detection, and the second is to do it on multiple wave signal. However I do not know how to merge them. Please help me

% Filename : endpoint1.m
  % Purpose : This function reads in a speech file and applies an endpoint
  % detection algorithm based on Short-term Energy and Zero-crossing Rate to determine
  % the speech boundaries.
  %
  function [datacropped,speechlength,speechflag] = endpoint1(s,fs,win,fl,inc);
  %
  % Endpoint Detection Using Short-term Energy and Zero-crossing Rate.
  % <Inputs>
  % datadir : Directory of the txt file containing speech signal.
  % fs : Sampling frequency in Hz (Default 8000).
  % win : Window type 'R' Rectangular window in time.
  % 'N' Hannning window in time.
  % 'H' Hamming window in time.
  % fl :Frame length (Default 80 samples corresponding to 10 ms).
  % inc :Increment in num of samples (Default 40).
  % <Outputs>
  % datacropped : This returns the cropped speech signal based on endpoint
  % detection.
  % speechflag : If any speechflag is set for warning any single one or
  % combination of the following problems might have occurred.
  % 1. Split data file may be corrupt if norm(s)<0.1
  % 2. Infinite loop in raw search algorithm for speech
  % boundaries if there is no signal detected that has 20 frames or longer
  % duration.
  % 3. Speech portion of the signal starting too early
  % might indicate a possible noise sequence in the beginning due to
  % bad recording.
  % All above cases need further investigation after cropping speech to determine if
  % the cropped data is corrupt.
  % speechlength : It is the length of the cropped speech signal.
  %
  % <References>
  % [1] L. R. Rabiner and M. R. Sambur, “An algorithm for determining the endpoints
  % of isolated utterances,” The Bell System Technical Journal, February 1975.
  %
  %------------------------------------------------------------------------------------------------------
  %clc, clear('s');
  if nargin < 2 fs = 8000; end
  if nargin < 3 win = 'R'; end % Default Rectangular Window.
  if nargin < 4 fl = fs/100; end % Default frame length is 80 for 10 ms.
  if nargin < 5 inc = fl/2; end % Default inc.in overlapping window is 40.
  if win == 'R'
  % Default Rectangular Window of length 80 for 10 ms frames.
  w = rectwin(fl);
  else if win =='N' w = hann(fl);
  else if win =='H' w = hamming(fl); end
   end
  end

    [s,fs]= wavread('KU_BARU.wav');
    %s=s(:,1)';

    %s = load(datadir);
    sm = s-mean(s); % Takes the mean out of data before processing.
    speechflag = 0;

    % IIR Elliptical BPF Design
    %d = fdesign.bandpass(100/4000,150/4000,2000/4000,2400/4000,60,0.5,60);
    %hd = ellip(d);
    %sf = filter(hd,sm); % Filters the speech data.

    % Design of a first-order pre-emphasis filter
    %a = 1;
    %b = [1, -15/16];
    %sf = filter(b,a,sm);

    % IIR Elliptical HPF Design
    d = fdesign.highpass('n,fst,fp,ap',10,60/4000,100/4000,0.5);
    hd = ellip(d);
    sf = filter(hd,sm);

    % Checking bad split trials below if any.
    if norm(sf) < 1.5; datacropped = []; speechflag = 1; speechlength = 0;
    else

    % Truncating the data to make it divisible by frame length.
    m = floor(length(sf)/inc);
    sf = sf(1:m*inc);

    % Short-term energy per frame is STE and Zero crossing count
    % per frame is ZCR. % 50 overlaping frames taken by default.
    for n=1:m-1;
     sw = sf(inc*(n-1)+1:inc*(n-1)+fl).*w; STE(n) = sum(abs(sw));
     for j= 2:fl;
        zc(j)=abs(sign(sw(j))-sign(sw(j-1)))/2;
     end
     ZCR(n) = sum(zc);
    end

    % Assuming there is no speech during the first 100 ms of recordings,
    % Mean and standard deviation of ZCR and STE for the first ten frames.
    avgzcr = mean(ZCR(1:10)); stdzcr = std(ZCR(1:10));
    avgste = mean(STE(1:10)); stdste = std(STE(1:10));

    % Setting up STE Upper and Lower Thresholds and ZCR Threshold.
    IF = fl/4; % 20 crossings per 10 ms is a fixed value when N=160;
    IZCT = min(IF,avgzcr+stdzcr); % Zero-crossing Rate Threshold.
    IE = 0.15; % Upper level for avgste in case high noise
    % present in first 20 frames.
    minste = min(IE,avgste+stdste);
    ITL = 8*minste; % Lower threshold for STE.
    ITU = 32*minste; % Upper threshold for STE.
    FT = (ITU-ITL)/2 + ITL; % Fine threshold for STE.

    % Following algorithm firsts makes a raw search for endpoint detection
    % based on STE, ITU and UTL. Then it refines the speech boundaries using
    % ZCR and IZCT for the successive and preceding 6 frames forth and back.
    % If the interval btwn rawstart and rawend is less than 100 ms (20 frames)
    % algorithm assumes that it is just a click noise (or a spike), not speech.

    duration = 0; rawend = 0; rawstart = 0; loopn =0; d = 1; refindex = 0;
    while duration < 80; % Raw search for speech boundaries starts.
     for n = d:m-1
      if STE(n) > ITU;
       refindex = n; rawstart = n;
       for l = refindex:-1.0:1
        if STE(l) < FT; rawstart = l; break; end
       end
     break;
    % If STE of speech signal does not exceed upper threshold, ITU is set to ITU = ITU/2
    % and makes one more search.
    else if n == m-1;
      ITU = ITU/2; FT = FT/2;
      for v = 1:m-1
       if STE(v) > ITU;

    refindex = v; rawstart = v;
      for p = refindex:-1.0:1   
        if STE(p) < FT; rawstart = p; break; end
      end
    break;
       end
      end
     end
     end
    end
    if refindex ~= 0;
    for k = refindex:m-1
     if STE(k) < FT; rawend = k; break; end
    end
    end
    duration = rawend - rawstart; % If duration < 20 frames, it keeps scanning.
    if (duration == 0); speechflag =2; break; end
    if (duration < 0); speechflag =3; break; end
    loopn = loopn+1;
    if loopn > 10; speechflag = 4; speechlength = 0; break; end % Prevents infinite loop.
    d = rawend+1;
    end

    % Fine search using total number of intervals crossing threshold of ZCR.
    finestart = rawstart; fineend = rawend;

    if (duration>23)&&(duration<50)
    nzc = 0; update = 0;
    if (rawstart-6) > 0;
    for n = rawstart:-1:(rawstart-6)
     if ZCR(n) > IZCT; nzc = nzc+1; update = n; end
    end
    if nzc > 3; finestart = update; end
    end

    nzc = 0; update = 0;
    if ((rawend+6) < length(ZCR))&&(rawend ~= 0);
    for n = rawend:(rawend+6)
     if ZCR(n) > IZCT; nzc = nzc+1; update = n; end
    end
     if nzc > 3; fineend = update; end
    end
    end

    starti = inc*(finestart)+1;
    endi = inc*(fineend);

    if (endi-starti) > 878;
    speechlength = endi-starti;
    datacropped = sf(starti:endi);
    speechflag = 0;
    else speechlength = 0; datacropped = sf;
    end

    %Plots of STE, ZCR, and original speech signal, thresholds and resulting
    %endpoints on the speech signal.
    % figure(1);
    % subplot(3,1,1); plot(STE); hold on,
    % subplot(3,1,1), plot(1:length(STE),ITU,'color','r'); hold on;
    % subplot(3,1,1), plot(1:length(STE),ITL,'color','g');
    % title('Abs. Magnitude Energy'); ylabel('Amplitude'); xlabel('Frame Number');
    % 
    % subplot(3,1,2); plot(ZCR); hold on;
    % subplot(3,1,2); plot(1:length(ZCR),IZCT,'color','r');
    % title('Zero-crossing Rate'); ylabel('Zero-crossings');
    % xlabel('Frame Number');
    % 
    % subplot(3,1,3); plot(s); hold on;
    % subplot(3,1,3); plot(starti,-2:0.1:2,'color','r'); hold on;
    % subplot(3,1,3); plot(endi,-2:0.1:2,'color','g');
    % title('kU_BARU(S101).wav'); ylabel('Amplitude');
    % xlabel('Sample Number');
    % 
    % figure(2);
    % subplot(2,1,1); plot(s(starti:endi)); title('Original Speech Cropped');
    % subplot(2,1,2); plot(sf(starti:endi)); title('KU_BARU(S101).wav'); % filtered speech cropped.
    % wavwrite(datacropped, fs,'KU_BARU(S101).wav')% the output signal
     end
    sound(datacropped,fs)
    %-----------------------------------------------------------------------------------------------------
    % End of function endpoint1.m
    %----------------------------------------------------------------------------------------------
The second function:

    fs=16000;
    filelist = dir('*.wav');
    % Pre-allocate a cell array to store some per-file information.
    result = cell(size(filelist));
    for index = 1 : length(filelist)
        fprintf('Processing %s\n', filelist(index).name);
        % Read the data of the WAV file and store it.
        s = wavread(filelist(index).name);
        [datacropped,speechlength,speechflag] = endpoint1(s,fs,'R',80,40);
        result{index} = datacropped;
    end
    % result{1} .. result{N} contain the data of the WAV files.
    %[datacropped,speechlength,speechflag] = endpoint1(fs,win,fl,inc)

Thanks a lot

[Dishant Arora]

What do you mean by merge , you want to have two scripts in same m file??

[Hamzah amee]

Hi Dishant..

Thanks for replying. What i meant is I want to call the function in the second script..

[Dishant Arora]

Put the later part of your code in another m script file and run it.

[Hamzah amee]

@Dishant Arora, Thanks..That is what I did..But thats is not the problem..the problem is in the code. However, I solved i already. However thanks for your opinion.