i m supposed to implement testing code for speech recognition..n getting error in line 154 as matrix dimensions must agree and 102 as index exceed matrix dimensions.....

        clc;
  clear all;
  close all;
  THRESHOLD=0.7;
  Fs = 10000;
  fprintf('say a sentence immediately after hitting enter: ');
  input('');
  y= wavrecord(1 * 10000, 10000, 'double'); % Record and store the uttered speech
  t=(0:(1*10000)-1)*1/(1*10000);
  subplot(5,1,1);
  plot(y);
  r=fft(y);
  d=abs(r);
  subplot(5,1,2);
  plot(d);
  z=floor(Fs/100);
  w=floor(Fs/5);%according to formula, 1600 sample needed for 8 khz
  %----------
  %calculation of mean and std
  h=[];
  for i=1:w
      h=[h y(i)];
  end
  meanVal=mean(h);
  sDev=std(h);
  %----------
  %identify voiced or not for each value
  for i=1:length(y)
     if(abs(y(i)-meanVal)/sDev > THRESHOLD)
         voiced(i)=1;
     else
         voiced(i)=0;
     end
  end

% identify voiced or not for each frame
%discard insufficient samples of last frame

usefulSamples=length(y)-mod(length(y),z);
frameCount=usefulSamples/z;
voicedFrameCount=0;
for i=1:frameCount
   cVoiced=0;
   cUnVoiced=0;
   for j=i*z-z+1:1:(i*z)
       if(voiced(j)==1)
           cVoiced=(cVoiced+1);
       else
           cUnVoiced=cUnVoiced+1;
       end
   end
   %mark frame for voiced/unvoiced
   if(cVoiced>cUnVoiced)
       voicedFrameCount=voicedFrameCount+1;
       voicedUnvoiced(i)=1;
   else
       voicedUnvoiced(i)=0;
   end
end

k=[];

%-----
for i=1:frameCount
    if(voicedUnvoiced(i)==1)
    for j=i*z-z+1:1:(i*z)
            k= [k y(j)];
        end
    end
end

%---display plot and play both sounds
    subplot(5,1,3);
    plot(k);
    g=fft(k);
    a=hamming(4000);% Hamming window to smooth the speech signal
    b= [a ;zeros(6000,1)];
    f = (1:10000);
    mel(f) = 2595 * log(1 + f / 700); % Linear to Mel frequency scale conversion
    tri = triang(100);
    win1 = [tri ; zeros(9900,1)]; % Defining overlapping triangular windows for
    win2 = [zeros(50,1) ; tri ; zeros(9850,1)]; % frequency domain analysis
    win3 = [zeros(100,1) ; tri ; zeros(9800,1)];
    win4 = [zeros(150,1) ; tri ; zeros(9750,1)];
    win5 = [zeros(200,1) ; tri ; zeros(9700,1)];
    win6 = [zeros(250,1) ; tri ; zeros(9650,1)];
    win7 = [zeros(300,1) ; tri ; zeros(9600,1)];
    win8 = [zeros(350,1) ; tri ; zeros(9550,1)];
    win9 = [zeros(400,1) ; tri ; zeros(9500,1)];
   win10 = [zeros(450,1) ; tri ; zeros(9450,1)];
   win11 = [zeros(500,1) ; tri ; zeros(9400,1)];
   win12 = [zeros(550,1) ; tri ; zeros(9350,1)];
   win13 = [zeros(600,1) ; tri ; zeros(9300,1)];
  win14 = [zeros(650,1) ; tri ; zeros(9250,1)];
  win15 = [zeros(700,1) ; tri ; zeros(9200,1)];
  win16 = [zeros(750,1) ; tri ; zeros(9150,1)];
  win17 = [zeros(800,1) ; tri ; zeros(9100,1)];
  win18 = [zeros(850,1) ; tri ; zeros(9050,1)];
  win19 = [zeros(900,1) ; tri ; zeros(9000,1)];
  win20 = [zeros(950,1) ; tri ; zeros(8950,1)]; 
ny = abs(g(floor(mel(f)))); % Mel warping
ny = ny / max(ny);
ny1 = ny * win1;
ny2 = ny * win2;
ny3 = ny * win3;
ny4 = ny * win4;
ny5 = ny * win5;
ny6 = ny * win6;
ny7 = ny * win7;
ny8 = ny * win8;
ny9 = ny * win9;
ny10 = ny * win10;
ny11 = ny * win11;
ny12 = ny *win12;
ny13 = ny * win13;
ny14 = ny * win14;
ny15 = ny * win15;
ny16 = ny * win16;
ny17 = ny * win17;
ny18 = ny * win18;
ny19 = ny * win19;
ny20 = ny * win20;
sy1 = sum(ny1 ^ 2); % Determine the energy of the signal within each window
sy2 = sum(ny2 ^ 2); % by summing square of the magnitude of the spectrum
sy3 = sum(ny3 ^ 2);
sy4 = sum(ny4 ^ 2);
sy5 = sum(ny5 ^ 2);
sy6 = sum(ny6 ^ 2);
sy7 = sum(ny7 ^ 2);
sy8 = sum(ny8 ^ 2);
sy9 = sum(ny9 ^ 2);
sy10 = sum(ny10 ^ 2);
sy11 = sum(ny11 ^ 2);
sy12 = sum(ny12 ^ 2);
sy13 = sum(ny13 ^ 2);
sy14 = sum(ny14 ^ 2);
sy15 = sum(ny15 ^ 2);
sy16 = sum(ny16 ^ 2);
sy17 = sum(ny17 ^ 2);
sy18 = sum(ny18 ^ 2);
sy19 = sum(ny19 ^ 2);
sy20 = sum(ny20 ^ 2);
sy = [sy1; sy2; sy3; sy4; sy5; sy6; sy7; sy8; sy9; sy10; sy11; sy12; sy13; sy14;
         sy15; sy16; sy17; sy18; sy19; sy20];
by = log(sy); 
dy = dct(by); % Determine DCT of Log of the spectrum energies 
subplot(5,1,4);
plot(dy);
fid = fopen('sample.dat','r'); 
dx = fread(fid,20, 'real*8'); % Obtain the feature vector for the password 
fclose(fid); % evaluated in the training phase  
dx=dx';
MSE=(sum((dx - dy) ^ 2)) / 20; % Determine the Mean squared error 
if MSE<1
    fprintf('\n\nACCESS GRANTED\n\n'); 
    Grant=wavread('Grant.wav'); % “Access Granted”
    wavplay(Grant); 
else
    fprintf('\n\nACCESS DENIED\n\n'); 
    Deny=wavread('Deny.wav'); % “Access Denied” is output in case of a failure
    wavplay(Deny);
end;

[Walter Roberson]

duplicate is at http://www.mathworks.com/matlabcentral/answers/29760-error-in-program-please-identify-the-error

Answer 1

[Walter Roberson]

Without calculating it through, I see no inherent reason to expect that

floor(2595 * log(1 + (1:10000) / 700))

will always be in the range 1:length(g) as g = fft(k) and k is built up conditionally based upon an unusual windowing function applied for "unvoiced" signals.