Help with speech recognition command

Everything is working in my example made by https://www.mathworks.com/help/deeplearning/examples/deep-learning-speech-recognition.html

If i try to write :

h = figure('Units','normalized','Position',[0.2 0.1 0.6 0.8]);

filterBank = designAuditoryFilterBank(fs,'FrequencyScale','bark',...
    'FFTLength',1024,...
    'NumBands',numBands,...
    'FrequencyRange',[50,7000]);

while ishandle(h)

    % Extract audio samples from the audio device and add the samples to
    % the buffer.
    x = audioIn();
    waveBuffer(1:end-numel(x)) = waveBuffer(numel(x)+1:end);
    waveBuffer(end-numel(x)+1:end) = x;

    % Compute the spectrogram of the latest audio samples.
    [~,~,~,spec] =  spectrogram(waveBuffer,hann(frameLength,'periodic'),frameLength - hopLength,512,'onesided');
    spec = filterBank * spec;
    spec = log10(spec + epsil);

    % Classify the current spectrogram, save the label to the label buffer,
    % and save the predicted probabilities to the probability buffer.
    [YPredicted,probs] = classify(trainedNet,spec,'ExecutionEnvironment','cpu');
    YBuffer(1:end-1)= YBuffer(2:end);
    YBuffer(end) = YPredicted;
    probBuffer(:,1:end-1) = probBuffer(:,2:end);
    probBuffer(:,end) = probs';

    % Plot the current waveform and spectrogram.
    subplot(2,1,1);
    plot(waveBuffer)
    axis tight
    ylim([-0.2,0.2])

    subplot(2,1,2)
    pcolor(spec)
    caxis([specMin+2 specMax])
    shading flat

    % Now do the actual command detection by performing a very simple
    % thresholding operation. Declare a detection and display it in the
    % figure title if all of the following hold:
    % 1) The most common label is not |background|.
    % 2) At least |countThreshold| of the latest frame labels agree.
    % 3) The maximum predicted probability of the predicted label is at
    % least |probThreshold|. Otherwise, do not declare a detection.
    [YMode,count] = mode(YBuffer);
    countThreshold = ceil(classificationRate*0.2);
    maxProb = max(probBuffer(labels == YMode,:));
    probThreshold = 0.7;
    subplot(2,1,1);
    if YMode == "background" || count<countThreshold || maxProb < probThreshold
        title(" ")
    else
        title(string(YMode),'FontSize',20)
    end

    drawnow

end

it gives me error :

> In designAuditoryFilterBank (line 104)

Error using DAGNetwork/calculatePredict>predictBatch (line 151)

Incorrect input size. The input images must have a size of [100 198 1].

Error in DAGNetwork/calculatePredict (line 17)

Y = predictBatch( ...

Error in DAGNetwork/classify (line 134)

scores = this.calculatePredict( ...

Error in SeriesNetwork/classify (line 502)

[labels, scores] = this.UnderlyingDAGNetwork.classify(X,

varargin{:});

After training i didnt change anything so i dont know how to fix it.