audio_reto.m

% Initialization
 clear
 close all
 clc
badSamples = 0;
fs2 = 44100;
while true
    %record audio
    audio = audiorecorder;
    disp('Start sampling.')
    recordblocking(audio, 10);
    disp('End of Sample.');

    %analyze it
    aFE3 = audioFeatureExtractor( ...
    SampleRate=fs2, ...
    Window=hamming(round(0.03*fs2),"periodic"), ...
    OverlapLength=round(0.02*fs2), ...
    linearSpectrum=true,...
    melSpectrum=true,...
    barkSpectrum=true,...
    mfcc=true, ...
    mfccDelta=true, ...
    mfccDeltaDelta=true, ...
    pitch=true, ...
    spectralCentroid=true, ...
    zerocrossrate=true, ...
    shortTimeEnergy=true,...
    spectralCentroid=true, ...
    spectralCrest=true, ...
    spectralDecrease=true, ...
    spectralEntropy=true, ...
    spectralFlatness=true, ...
    spectralFlux=false, ...
    spectralKurtosis=true, ...
    spectralRolloffPoint=true, ...
    spectralSkewness=true, ...
    spectralSlope=true, ...
    spectralSpread=true,...
    harmonicRatio=true);

    features3 = extract(aFE3,audio.getaudiodata);
    idx3 = info(aFE3);

    q1=features3(:,idx3.spectralEntropy);
    q2=features3(:,idx3.zerocrossrate);
    n = length(q2);
    thresholdN = n * .30;
    badSamples = 0;
%     plot(q1,q2,'r*')
%     xlabel('entropy'); 
%     ylabel('pitch')

%     check if error
    for i = 1 : n
        if q1(i) < 0.7 && q2(i) > 0.02
            badSamples = badSamples + 1;
        end
    end
    if badSamples > thresholdN
        disp('State: Critical');
    else
        disp('State: Normal');
    end
%     disp(badSamples);
end