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

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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);

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