Converting a set of audio signals to images and saving them.

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omid
omid 2023-2-6
回答： DGM 2023-2-6
Hello friends. I want to do spectral conversion on my audio signals and then save the output images somewhere else. But I don't know how to read and write in the images.
% make a list of wave files in training_data folder
cd training_data_out\
folderInfo = dir('**/*.wav');
folderInfo1 = dir('**/*.tsv');
folderInfo2 = dir('**/*.txt');
cd ..\
addpath training_data_out\
% fir bandpass filter design with fc1 = 20/fs/2 and fc2 = 500/fs/2 with
% fs=4000
f = [0 0.005 0.015 0.245 0.255 1];
a = [0 0 1 1 0 0];
b = firpm(100,f,a);
% feature vector calculation
for i=1:length(folderInfo)
x = audioread(folderInfo(i).name);
% signal filtering
xf = filter(b,1,x);
[st,t,f]=st(xf,25,350,1,1);
m=abs (st);
imagesc(m (:,:,i))
pause(.5)
end
  1 个评论
Jan
Jan 2023-2-6
"But I don't know how to read and write in the images." - use imread and imwrite.
Avoid to add a folder to Matlab's path only to read or write some files. This is a source of unexpected behavior, if the folders contain m-files. Use full paths instead and do not change the current folder:
folder = cd; % Or prefer an absolute path here also
folderInfo = dir(fullfile(folder, 'training_data_out', '**/*.wav');
Remember that cd() commands can be called unexpectedly in callbacks of timers or GUIs during your code runs. This is a typical source of bugs and can be avoided easily.

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回答（1 个）

DGM
DGM 2023-2-6
I don't know what st() is, but I have to assume it's a function -- possibly an STFT tool? If so, then it won't be a function anymore. You've just created a variable with the same name.
[st,t,f]=st(xf,25,350,1,1);
If that's a correct assumption, then I'd expect st to be a 2D array. I would have no reason to expect that each file would produce a 3D array with as many pages as there are audio files in the directory. So I'd have to conclude that this isn't the way to address m.
imagesc(m(:,:,i))
To generate a pseudocolored image from real-valued data on an arbitrary scale:
% a page
st = 10*randn(100,100); % random fake data (2D)
st = abs(st);
% convert to an RGB image using uniform quantization
N = 256; % specify quantization levels
CT = jet(N); % specify colormap to use
outpict = ind2rgb(gray2ind(mat2gray(st),N),CT);
% do something with it
imshow(outpict)
imwrite(outpict,'myimage.png')
Just a guess, but this may be relevant. Sometimes similar questions pop up at the same time when multiple people are working on the same assignment.
https://www.mathworks.com/matlabcentral/answers/1906355-conversion-of-129x7-complex-double-to-an-image

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