
clear; %load an audio [x,fs]=audioread('example.wav'); %windowing data win=round(0.025890625*fs); over=round(0.01875*fs); % 72% %Obtain the spectral data [s, f, t]=spectrogram(... x,... hamming(win),... over,... win,fs,'yaxis'); slope_normal(:,1)=spectralSlope(x,fs, Window=hamming(win),OverlapLength=over); slope_spec(:,1)=spectralSlope(s,f); figure;plot(slope_normal);hold on;plot(slope_sub);
%% Compare Time-Domain and Frequency-Domain Inputs [x,fs] = audioread('Counting-16-44p1-mono-15secs.wav'); % Define window and overlap length windowLength = round(0.025890625*fs); overlapLength = round(0.01875*fs); win = hamming(windowLength); fftLength = windowLength; % Calculate the power spectrum the same was as the spectral descriptors [~,f,~,ps] = spectrogram( ... x, ... win, ... overlapLength, ... fftLength,fs,'yaxis','power','onesided'); % Slope using time domain input slope_timeDomainInput = spectralSlope(x,fs, ... Window=win,OverlapLength=overlapLength,SpectrumType='power'); % Slope using frequency domain input slope_frequencyDomainInput = spectralSlope(ps,f); figure(1) plot(slope_timeDomainInput,'ro');hold on plot(slope_frequencyDomainInput,'b*');hold off title("Error = " +rms(slope_timeDomainInput - slope_frequencyDomainInput))
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