Similarity of two .wav files - unsure about the returned error.
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Taylor Gray
el 11 de Abr. de 2019
Comentada: Taylor Gray
el 13 de Abr. de 2019
Hi, I'm wanting to use correlation to see how similar an original sound and one I synthesized from it are. I was advised to use the resample function however, due to lack of knowledge in MATLAB I'm looking for a little help to gain my metric as I'm just not understanding things. I have attached the audio files if anyone could please help me out a little?
clear, clc, close all
% get a section of the sound file
[x, fs] = audioread('Machine_Gun.wav'); % load an audio file
x = x(:, 1); % get the first channel
N = length(x); % signal length
t = (0:N-1)/fs; % time vector
[y, fs] = audioread('Dry_Synthesized_Machine_Gun.wav'); % load an audio file
y = y(:, 1); % get the first channel
n = length(y); % signal length
T = (0:n-1)/fs;
data = [x y];
correlation = corrcoef(data);
This was my failed attempt and i got the below error message:
Error using horzcat
Dimensions of arrays being concatenated are not consistent.
Error in test (line 12)
data = [x y];
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Jan
el 11 de Abr. de 2019
Editada: Jan
el 11 de Abr. de 2019
Error using horzcat
Dimensions of arrays being concatenated are not consistent.
data = [x y];
This means the x and y have a different number of elements. Then a horizontal concatenation cannot work, because matrices must be rectangular.
You have mentioned resample already, which allows to adjust the sizes of the vectors. interp1 would be fine also. But this would change the frequency of the signal. Maybe cropping or appending zeros is better:
% get a section of the sound file
[x, fsx] = audioread('Machine_Gun.wav'); % load an audio file
[y, fsy] = audioread('Dry_Synthesized_Machine_Gun.wav'); % load an audio file
x = x(:, 1); % get the first channel
y = y(:, 1); % get the first channel
nx = length(x); % signal length
ny = length(y); % signal length
yPad = y;
yCrop = y;
xPad = x;
xCrop = x;
if nx > ny
yPad(nx) = 0;
xCrop = xCrop(1:ny);
elseif nx < ny
xPad(ny) = 0;
yCrop = yCrop(1:nx);
end
c1 = corrcoef(xPad, yPad);
c2 = corrcoef(xCrop, yCrop);
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