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

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studentmatlaber 2022-5-30

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1730190-how-can-i-make-an-example-of-denoise-speech-using-deep-learning-networks-with-rnn

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);