How can I make an example of Denoise Speech Using Deep Learning Networks with RNN?

3 次查看(过去 30 天)
I want to repeat the example in the link with RNN. But I couldn't figure out exactly what changes I need to make. First I added lstmLayer. I understand that I need to use sequenceInputLayer instead of imageInputLayer. What else do I need to change?
numHiddenUnits=100;
layers = [
sequenceInputLayer([numFeatures,numSegments])
lstmLayer(numHiddenUnits,'OutputMode','last')
batchNormalizationLayer
reluLayer
fullyConnectedLayer(1024)
batchNormalizationLayer
reluLayer
fullyConnectedLayer(numFeatures)
regressionLayer
];
miniBatchSize = 128;
options = trainingOptions("adam", ...
"MaxEpochs",3, ...
"InitialLearnRate",1e-5,...
"MiniBatchSize",miniBatchSize, ...
"Shuffle","every-epoch", ...
"Plots","training-progress", ...
"Verbose",false, ...
"ValidationFrequency",floor(size(trainPredictors,4)/miniBatchSize), ...
"LearnRateSchedule","piecewise", ...
"LearnRateDropFactor",0.9, ...
"LearnRateDropPeriod",1, ...
"ValidationData",{validatePredictors,validateTargets});
denoiseNetFullyConnected = trainNetwork(trainPredictors,trainTargets,layers,options);

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 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