matlab 深度学习做声音分类

Posted 2022-10-22

1、内容简介

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深度学习做声音分类

2、内容说明

提取声音特征，然后通过CNN进行分类

3、仿真分析

[normal_01_L,~] = audioread(正常样本2s_01_L.wav);
[normal_02_L,~] = audioread(正常样本2s_02_L.wav);
 [qikong_01_L,fs] = audioread(气孔样本2s_01_L.wav);len = 8e4;
numTrain = 800;
 audioTrain = [data_1(:,1:numTrain),data_2(:,1:numTrain),data_3(:,1:numTrain)];
 labelsTrain = [data_1_Label(1:numTrain);data_2_Label(1:numTrain);data_3_Label(1:numTrain)];audioValidation = [data_1(:,numTrain+1:end),data_2(:,numTrain+1:end),data_3(:,numTrain+1:end)];
 labelsValidation = [data_1_Label(numTrain+1:end);data_2_Label(numTrain+1:end);data_3_Label(numTrain+1:end)]; aFE = audioFeatureExtractor("SampleRate",fs, ...
     "SpectralDescriptorInput","melSpectrum", ...
     "spectralCentroid",true, ...
     "spectralSlope",true); featuresTrain = extract(aFE,audioTrain);
 [numHopsPerSequence,numFeatures,numSignals] = size(featuresTrain)featuresTrain = permute(featuresTrain,[2,1,3]);
 featuresTrain = squeeze(num2cell(featuresTrain,[1,2]));numSignals = numel(featuresTrain)
[numFeatures,numHopsPerSequence] = size(featuresTrain1)
featuresValidation = extract(aFE,audioValidation);
 featuresValidation = permute(featuresValidation,[2,1,3]);
 featuresValidation = squeeze(num2cell(featuresValidation,[1,2]));layers = [ ...
     sequenceInputLayer(numFeatures)
     lstmLayer(50,"OutputMode","last")
     fullyConnectedLayer(numel(unique(labelsTrain)))
     softmaxLayer
     classificationLayer];options = trainingOptions("adam", ...
     "Shuffle","every-epoch", ...
     "ValidationData",featuresValidation,labelsValidation, ...
     "Plots","training-progress", ...
     "MaxEpochs", 100,...
     "Verbose",false);net = trainNetwork(featuresTrain,labelsTrain,layers,options);

 

4、参考论文

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