Deep Neural Network Tranining

Hi,

I am having trouble in running the modified DeepLearningSpeechRecognitionExample_all that utilzis all the data:

"bird",...

"cat",...

"dog",...

"down",...

"eight",...

"five",...

"four",...

"happy",...

"house",...

"left",...

"marvin",...

"nine",...

"one",...

"right",...

"seven",...

"sheila",...

"six",...

"stop",...

"three",...

"two",...

"zero",...

"bed",...

"go",...

"no",...

"off",...

"on",...

"tree",...

"up",...

"wow",...

and modifyed parametrs in training (double number of feature vectors) that is:

segmentDuration = 1;

frameDuration = 0.020; %0.025;

hopDuration = 0.005; %0.010; <---------------- doubleing the sigze of feature vectors

numBands = 40; %40;

as well as more layers of neural network and larger feature vector size.

numF = 40; %12;

layers = [

imageInputLayer(imageSize)

convolution2dLayer(3,numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,2*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,3*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,4*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,5*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,4*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,3*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,2*numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

maxPooling2dLayer(3,'Stride',2,'Padding','same')

convolution2dLayer(3,numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

convolution2dLayer(3,numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

convolution2dLayer(3,numF,'Padding','same')

batchNormalizationLayer

reluLayer

%tanhLayer

dropoutLayer(dropoutProb)

fullyConnectedLayer(numClasses)

softmaxLayer

weightedClassificationLayer(classWeights)];

The code fials with this error:

...done

Training error: 1.2073%

Validation error: 3.8136%

Network size: 4772.4043 kB

Error using classify (line 149)

The length of GROUP must equal the number of rows in TRAINING.

Error in DeepLearningSpeechRecognitionExample_all (line 457)

[YPredicted,probs] = classify(1,x,"ExecutionEnvironment",'cpu');

I need a profesional help to figure out why am getting the length difference? Note that the reson why I am not able to track that problem down is due to the fact that this program requires at least a half-day to run in my computer before it failes.

Thank you

--Veton

[Piyush Dubey]

Refer to this answer.