Merge branch 'featureSpectAnalysis' into develop

FT_times.m

@@ -0,0 +1,21 @@
+clear all
+close all
+clc
+
+[y, fs] = audioread("sound/modulator22.wav");
+times = [];
+item_num = 20;
+for j = 1:item_num
+  localtime = [];
+  for i = 0:1
+    t0 = clock ();
+    frequencySpectrum_noplot(y, fs, 0); %true does FFT, false DFT
+    localtime(i+1) = etime (clock (), t0);
+  endfor
+  times = [times; localtime];
+endfor
+
+printf('Average DFT time: %d \n', mean(times(1:item_num, 1)))
+printf('Standard deviation of DFT time: %d \n', std(times(1:item_num, 1)))
+printf('Average FFT time: %d \n', mean(times(1:item_num, 2)))
+printf('Standard deviation of FFT time: %d \n', std(times(1:item_num, 2)))

frequencySpectrum_noplot.m

@@ -0,0 +1,44 @@
+function [power, duration] = frequencySpectrum_noplot(signal, fs, pad)
+%%%%%%%%%%%%%%%%%%
+%function power = frequencySpectrum(signal, fs, pad)
+%
+% Task: Display the power spectrum (lin and log scale) of a given signal
+%
+% Input:
+%	- signal: the input signal to process
+%	- fs: the sampling rate
+%	-pad: boolean if true, signal is padded with 0 to the next power of 2 -> FFT instead of DFT
+%
+% Output: 
+%	- power: the power spectrum
+%	
+%
+% Guillaume Gibert, guillaume.gibert@ecam.fr
+% 25/04/2022
+%%%%%%%%%%%%%%%%%%
+
+n = length(signal);        % number of samples
+
+if (pad)
+	n = 2^nextpow2(n);
+end
+
+tic
+y = fft(signal, n);% compute DFT of input signal
+duration = toc;
+
+power = abs(y).^2/n;    % power of the DFT
+
+[val, ind] = max(power); % find the mx value of DFT and its index
+
+t=0:1/fs:(n-1)/fs; % time range
+%pad signal with zeros
+if (pad)
+	signal = [ signal; zeros( n-length(signal), 1)];
+end
+
+f = (0:n-1)*(fs/n);     % frequency range
+
+
+
+

spectral_analysis.m

@@ -0,0 +1,46 @@
+clear all
+close all
+clc
+
+[y, fs] = audioread("sound/modulator22.wav");
+ranges = [17000, 20000; 29000, 37000; 41000, 46000];
+one = y(ranges(1,1):ranges(1,2));
+two = y(ranges(2,1):ranges(2,2));
+three = y(ranges(3,1):ranges(3,2));
+
+word = one;
+
+n = length(word);   
+f = (0:n-1)*(fs/n);
+f1 = 0;%Hz
+f2 = 4000;%Hz
+idx = find(f >= f1 & f <= f2); %define the index of the freq range
+f = f(idx);
+y = fft(word, n);% compute DFT of input signal
+power = abs(y).^2/n;
+power = power(idx);
+[val, ind] = max(power);
+
+%lowpass for the formant
+
+Fc = 2000; % define the cutoff frequency of the low-pass filter
+[b, a] = butter(6, Fc/(fs/2), 'low'); % design a 4th-order Butterworth low-pass filter
+Pxx_filt = filter(b, a, power); % apply the filter to the power spectrum
+length(Pxx_filt)
+length(f)
+
+
+figure;
+
+subplot(1,2,1) % time plot 
+plot(0:1/fs:(length(word)-1)/fs,word);
+xlabel('Time (s)');
+ylabel('Amplitude (a.u.)');
+
+subplot(1,2,2) % freq range plot 
+plot(f,10*log10(power/power(ind))); hold on;
+plot(f, 10*log10(Pxx_filt), 'r');
+xlabel('Frequency (Hz)')
+ylabel('Power (dB)')
+
+

spectrogram_analysis.m

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+clear all
+close all
+clc
+
+[y, fs] = audioread("sound/modulator22.wav");
+step_size = 5; %ms
+window_size = 30;%ms, ideal value 25
+spectrogram(y, fs, step_size, window_size)