Audio data loading and splitting

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Divya
Divya 2025-3-6
评论： Mathieu NOE 2025-4-2
How to load the audio dataset with subfolders in pwd, create ads and spilt them into train and testing set

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Mathieu NOE
Mathieu NOE 2025-3-6
hello
see example below - adapt to you own needs
%% Important Notice :
% NB : wav files are not searched inside the main folder (yourpath) but only in subfolders (dirnames)
% in other words : this code works for wav files that are only located in
% subfolders , not in the main "yourpath" folder
% if S is empty that means no data file exist (matching the file filter in the searched subfolder)
%% define path
yourpath = pwd; % or your specific path
list=dir(yourpath); %get info of files/subfolders in current directory
isfile=~[list.isdir]; %determine index of files vs folders
dirnames={list([list.isdir]).name}; % directories names (including . and ..)
dirnames=dirnames(~(strcmp('.',dirnames)|strcmp('..',dirnames))); % remove . and .. directories names from list
%% FFT options
% if you are dealing with acoustics, you may wish to have A weighted
% spectrums / spectrograms
% option_w = 0 : linear spectrum (no weighting dB (L) )
% option_w = 1 : A weighted spectrum (dB (A) )
option_w = 0;
% spectrogram dB scale
spectrogram_dB_scale = 80; % the lowest displayed level is XX dB below the max level
NFFT = 512; % fft buffer size
OVERLAP = 0.75; % percentage of overlap (1 = 100%)
%% Loop on each folder
for ci = 1:length(dirnames) %
fileDir = char(dirnames(ci)); % current directory name
S = dir(fullfile(fileDir,'*.wav')); % get list of data files in directory according to name structure 'Sheeta*.xlsx'
S = natsortfiles(S); % sort file names into natural order (what matlab dir does not well) , see FEX :
%(https://fr.mathworks.com/matlabcentral/fileexchange/47434-natural-order-filename-sort)
%% Loop inside folder
for k = 1:length(S) % read data in specified sheet
[signal,Fs] = audioread(fullfile(fileDir, S(k).name)); % or use a structure (S(k).data ) to store the full data structure
dt = 1/Fs;
[samples,channels] = size(signal);
time = (0:samples-1)*dt; % time vector
title_str = [fileDir ' / ' S(k).name];
title_str = strrep(title_str,'_',' '); % replace underscores with blanks for better rendering
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% spectrogram demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for ck = 1:channels
[sg,fsg,tsg] = specgram(signal(:,ck),NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));
tsg = tsg + NFFT/(2*Fs); % small time correction so that a fft buffer is time referenced at the buffer middle point
% 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
% apply A weigthing if needed
if option_w == 1
pondA_dB = pondA_function(fsg);
sg_dBpeak = sg_dBpeak+(pondA_dB*ones(1,size(sg_dBpeak,2)));
my_title = ('Spectrogram (dB (A))');
else
my_title = ('Spectrogram (dB (L))');
end
% saturation of the dB range : 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();
ah1 = subplot(3,1,1);
plot(time,signal(:,ck));
xlim([min(time) max(time)]); % make sure time and spectrogram have same x axis
title(title_str); % time domain plot (one channel)
xlabel('Time (s)');
ylabel('Amplitude');
ah2 = subplot(3,1,2:3);
imagesc(tsg,fsg,sg_dBpeak);colormap('jet'); % spectrogram plot (one channel)
xlim([min(time) max(time)]); % make sure time and spectrogram have same x axis
axis('xy');grid on
hcb = colorbar('vert');
set(get(hcb,'Title'),'String','dB')
%# find current position [x,y,width,height]
pos2 = get(ah2,'Position');
pos1 = get(ah1,'Position');
%# set width of second axes equal to first
pos2(3) = pos1(3);
set(ah2,'Position',pos2)
df = fsg(2)-fsg(1); % freq resolution
title([my_title ' / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(df,3) ' Hz / Channel : ' num2str(ck)]);
xlabel('Time (s)');
ylabel('Frequency (Hz)');
end
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% A weighting for acoustic FFT Analysis
function pondA_dB = pondA_function(f)
% dB (A) weighting curve
n = ((12200^2*f.^4)./((f.^2+20.6^2).*(f.^2+12200^2).*sqrt(f.^2+107.7^2).*sqrt(f.^2+737.9^2)));
r = ((12200^2*1000.^4)./((1000.^2+20.6^2).*(1000.^2+12200^2).*sqrt(1000.^2+107.7^2).*sqrt(1000.^2+737.9^2))) * ones(size(f));
pondA = n./r;
pondA_dB = 20*log10(pondA(:));
end

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