How to use trainNetwork with transform datastore with multiple outputs?

11 次查看(过去 30 天)
my code create a audioDataStore, transform it to yamnet features (mel spectrum) and try to train it.
But i get the following error:
Input datastore returned more than one observation per row for network input 1.
The code:
net = yamnet;
DS = audioDatastore(FolderName, ...
'FileExtensions',{'.wav','.mp3'},"IncludeSubfolders",true,'LabelSource','foldernames');
DS.Labels = setcats(DS.Labels,cellstr(net.Layers(86).Classes));
TR = transform(DS,@(audio,info)preProcess(audio,info),"IncludeInfo",true);
options = trainingOptions("adam");
trainNetwork(TR,net.Layers,options)
function [data,info] = preProcess(audio,info)
data{1} = yamnetPreprocess(audio,info.SampleRate);
data{2} = repmat(info.Label,1,size(data{1},4));
end
Yamnet produce multiple observations for each audio file (for instance, for 10 seconds file it will create 96×64×1×19 matrix which are 19 observations. For some reason trainNetwork want only one observation, how do I fix it?

采纳的回答

jibrahim
jibrahim 2023-2-9
Hi Noam,
Check out this example:
The example uses a transformed datastore as well. the transformation function is at the bottom:
function [data,info] = audioPreprocess(audioIn,info)
class = info.Label;
fs = info.SampleRate;
features = yamnetPreprocess(audioIn,fs);
numSpectrograms = size(features,4);
data = cell(numSpectrograms,2);
for index = 1:numSpectrograms
data{index,1} = features(:,:,:,index);
data{index,2} = class;
end
end

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Pretrained Models 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by