MATLAB: Extracting the fundamental frequency of a .wav file

audiofourierfundamental frequencyspectrum

I have a .wav file, which I read with wavread and later do the fft.

If Y=fft(y,N), being y the vector with the samples of the .wav file and Y the fourier transformation of y.

How can I make a relation between the frequencies and the samples of Y? I want to get the frequency in wich Y has the highest value.

Thanks.

Best Answer

Here is an example you can modify with your input y

For even length y:

    Fs = 1000;
    t = 0:0.001:1-0.001;
    y = cos(2*pi*100*t)+randn(size(t));
    ydft = fft(y);
    freq = 0:Fs/length(y):Fs/2;
    ydft = ydft(1:length(y)/2+1);
    plot(freq,abs(ydft))
    [maxval,idx] = max(abs(ydft));
    freq(idx)  %this is frequency corresponding to max value

For odd length y

    t = 0:0.001:1;
    y = cos(2*pi*100*t)+randn(size(t));
    ydft = fft(y);
    freq = 0:Fs/length(y):Fs/2;
    ydft = ydft(1:floor(length(y)/2)+1);
    [maxval,idx] = max(abs(ydft));
    freq(idx)  %this is frequency corresponding to max value

Related Solutions

MATLAB: How to find max freq and lamdha min for a pulse

   ydft = fft(y);
   ydft = ydft(1:floor(length(ydft)/2)+1);
   [maxval,I] = max(abs(ydft));
   freq = 0:fs/length(y):fs/2;
   fprintf('Maximum at %2.3f Hz\n.', freq(I));

You would have been better with:

   t=0:ts:n/f-ts;
   y=15*(1-cos(2*pi*f*t/n)).*cos(2*pi*f*t);
   ydft = fft(y);
   ydft = ydft(1:length(ydft)/2+1);
   [maxval,I] = max(abs(ydft));
   freq = 0:fs/length(y):fs/2;
   fprintf('Maximum at %2.3f Hz\n.', freq(I));

Due to the spacing of the frequencies in the DFT. As far as the wavelength, you have not told us the propagation speed, which you have to in order to determine wavelength. If we assume that it is the speed of light, then

lambda = 3e8/freq(I);
fprintf('Wavelength is %3.2f meters.\n',lambda)

MATLAB: Manual spectrogram creation without using spectrogram command

hello

see below (myspecgram)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%





% load signal
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% data
[data,Fs] = audioread('myWAVaudiofile.wav');
channel = 1;
signal = data(:,channel);
samples = length(signal);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% FFT parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
NFFT = 4096;    % 
OVERLAP = 0.75;
% spectrogram dB scale
spectrogram_dB_scale = 100;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% options 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% decimate (if needed)
% NB : decim = 1 will do nothing (output = input)
decim = 2;
if decim>1
    signal = decimate(signal,decim);
    Fs = Fs/decim;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% display 2 : time / frequency analysis : spectrogram demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [sg,fsg,tsg] = specgram(signal,NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));  
[sg,fsg,tsg] = myspecgram(signal,NFFT,Fs,OVERLAP);  
% FFT normalisation and conversion amplitude from linear to dB (peak)
sg_dBpeak = 20*log10(abs(sg))+20*log10(2/length(fsg));     % NB : X=fft(x.*hanning(N))*4/N; % hanning only
% saturation of the dB range : 
% saturation_dB = 60;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
min_disp_dB = round(max(max(sg_dBpeak))) - spectrogram_dB_scale;
sg_dBpeak(sg_dBpeak<min_disp_dB) = min_disp_dB;
% plots spectrogram
figure(2);
imagesc(tsg,fsg,sg_dBpeak);colormap('jet');
axis('xy');colorbar('vert');grid
title([' Spectrogram / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(fsg(2)-fsg(1)) ' Hz ']);
xlabel('Time (s)');ylabel('Frequency (Hz)');
function  [sg,freq_vector,time] = myspecgram(signal,nfft,Fs,Overlap)
% [sg,freq_vector,time] = myspecgram(signal,NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));
% FFT peak spectrogram of signal  (example sinus amplitude 1   = 0 dB after fft).
%   signal - input signal, 
%   Fs - Sampling frequency (Hz).
%   nfft - FFT window size
%   Overlap - buffer overlap % (between 0 and 0.95)
dt = 1/Fs;
signal = signal(:);
samples = length(signal);
% fill signal with zeros if its length is lower than nfft
if samples<nfft
    s_tmp = zeros(nfft,1);
    s_tmp((1:samples)) = signal;
    signal = s_tmp;
    samples = nfft;
end
% window : hanning
window = hanning(nfft);
window = window(:);
%    compute fft with overlap 
 offset = fix((1-Overlap)*nfft);
 spectnum = 1+ fix((samples-nfft)/offset); % Number of windows
%     % for info is equivalent to : 
%     noverlap = Overlap*nfft;
%     spectnum = fix((samples-noverlap)/(nfft-noverlap));	% Number of windows
    % main loop
    sg = [];
    for i=1:spectnum
        start = (i-1)*offset;
        sw = signal((1+start):(start+nfft)).*window;
        sg = [sg (abs(fft(sw))*4/nfft)];     % X=fft(x.*hanning(N))*4/N; % hanning only 
        time(i) = (start+nfft/2)*dt; % time defined as in the middle of the data buffer
    end
% one sidded fft spectrum  % Select first half 
    if rem(nfft,2)    % nfft odd
        select = (1:(nfft+1)/2)';
    else
        select = (1:nfft/2+1)';
    end
    
sg = sg(select,:);
freq_vector = (select - 1)*Fs/nfft;
end

Best Answer

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MATLAB: How to find max freq and lamdha min for a pulse

MATLAB: Manual spectrogram creation without using spectrogram command

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