Hi David,
Please find below a possible solution that uses Audio Toolbox functionality. It uses a sample dataset as an example.
% Download the Free Spoken Digit Data Set (FSDD).
% FSDD consists of 2000 recordings of four speakers saying the numbers 0
% through 9 in English.
downloadFolder = matlab.internal.examples.downloadSupportFile("audio","FSDD.zip");
dataFolder = tempdir;
unzip(downloadFolder,dataFolder)
dataset = fullfile(dataFolder,"FSDD");
% Create an audioDatastore that points to the dataset.
ads = audioDatastore(dataset,IncludeSubfolders=true);
% Create a transformed datastore that computes spectra from audio data.
% Here, use pwelch.
adsSpec = transform(ads,@(x)pwelch(x,'power'));
% Use writeall to write spectra to disk. Set UseParallel to
% true to perform writing in parallel.
outputLocation = fullfile(tempdir,"MyFeatures");
writeall(adsSpec,outputLocation,WriteFcn=@myCustomWriter,UseParallel=true);
% Create a signalDatastore that points to the out-of-memory features. The
% read function returns a spectrum/timestamp pair.
sds = signalDatastore(outputLocation,IncludeSubfolders=true, ...
SignalVariableNames=["spec","timestamp"],ReadOutputOrientation="row");
% Read one pair of spectrum/timestamp
y = read(sds)
% Create a tall table
t = tall(sds);
function myCustomWriter(spec,writeInfo,~)
% myCustomWriter(spec,writeInfo,~) writes spectra/time stamps
% pair to MAT files.
filename = strrep(writeInfo.SuggestedOutputName,".wav",".mat");
% also write a time stamp as an example
timestamp = datetime('now');
save(filename,"spec","timestamp");
end
