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function y = chanvocoder(carrier, modul, chan, numband, overlap)
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% y = chanvocoder(carrier, modul, chan, numband, overlap)
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% The Channel Vocoder modulates the carrier signal with the modulation signal
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% chan = number of channels (e.g., 512)
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% numband = number of bands (<chan) (e.g., 32)
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% overlap = window overlap (e.g., 1/4)
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if numband>chan
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error('# bands must be < # channels')
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end
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[rc, cc] = size(carrier);
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if cc>rc
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carrier = carrier';
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end
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[rm, cm] = size(modul);
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if cm>rm
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modul = modul';
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end
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st = min(rc,cc); % stereo or mono?
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if st~= min(rm,cm)
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error('carrier and modulator must have same number of tracks');
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end
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len = min(length(carrier),length(modul)); % find shortest length
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carrier = carrier(1:len,1:st); % shorten carrier if needed
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modul = modul(1:len,1:st); % shorten modulator if needed
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L = 2*chan; % window length/FFT length
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w = hanning(L);
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if st==2
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w=[w w];
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end % window/ stereo window
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bands = 1:round(chan/numband):chan; % indices for frequency bands
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bands(end) = chan;
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y = zeros(len,st); % output vector
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ii = 0;
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while ii*L*overlap+L <= len
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ind = round([1+ii*L*overlap:ii*L*overlap+L]);
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FFTmod = fft( modul(ind,:) .* w ); % window & take FFT of modulator
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FFTcar = fft( carrier(ind,:) .* w ); % window & take FFT of carrier
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syn = zeros(chan,st); % place for synthesized output
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for jj = 1:numband-1 % for each frequency band
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b = [bands(jj):bands(jj+1)-1]; % current band
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syn(b,:) = FFTcar(b,:)*diag(mean(abs(FFTmod(b,:))));
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end % take product of spectra
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midval = FFTmod(1+L/2,:).*FFTcar(1+L/2,:); % midpoint is special
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synfull = [syn; midval; flipud( conj( syn(2:end,:) ) );]; % + and - frequencies
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timsig = real( ifft(synfull) ); % invert back to time
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y(ind,:) = y(ind,:) + timsig; % add back into time waveform
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ii = ii+1;
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end
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y = 0.8*y/max(max(abs(y))); % normalize output
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function [power, duration] = frequencySpectrum(signal, fs, pad)
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%%%%%%%%%%%%%%%%%%
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%function power = frequencySpectrum(signal, fs, pad)
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%
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% Task: Display the power spectrum (lin and log scale) of a given signal
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%
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% Input:
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% - signal: the input signal to process
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% - fs: the sampling rate
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% -pad: boolean if true, signal is padded with 0 to the next power of 2 -> FFT instead of DFT
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%
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% Output:
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% - power: the power spectrum
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%
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%
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% Guillaume Gibert, guillaume.gibert@ecam.fr
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% 25/04/2022
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%%%%%%%%%%%%%%%%%%
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n = length(signal); % number of samples
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if (pad)
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n = 2^nextpow2(n);
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end
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tic
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y = fft(signal, n);% compute DFT of input signal
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duration = toc;
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power = abs(y).^2/n; % power of the DFT
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[val, ind] = max(power); % find the mx value of DFT and its index
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% plots
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figure;
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subplot(1,3,1) % time plot
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t=0:1/fs:(n-1)/fs; % time range
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%pad signal with zeros
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if (pad)
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signal = [ signal; zeros( n-length(signal), 1)];
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end
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plot(t, signal)
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xticks(0:0.1*fs:n*fs);
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xticklabels(0:0.1:n/fs);
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xlabel('Time (s)');
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ylabel('Amplitude (a.u.)');
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subplot(1,3,2) % linear frequency plot
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f = (0:n-1)*(fs/n); % frequency range
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plot(f,power, 'b*'); hold on;
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plot(f,power, 'r');
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xlabel('Frequency (Hz)')
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ylabel('Power (a.u.)')
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subplot(1,3,3) % log frequency plot
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plot(f,10*log10(power/power(ind)));
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xlabel('Frequency (Hz)')
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ylabel('Power (dB)')
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fig =gcf;
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set(fig, 'Visiblr', 'off');
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function spectrogram(signal, samplingFreq, step_size, window_size)
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%%%%%%%%%%%%%%%%%%%%%%%
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%function spectrogram(signal, samplingFreq, step_size, window_size)
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% ex.: spectrogram(signal, samplingFreq, step_size, window_size)
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%
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% Task: Plot the spectrogram of a given signal
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%
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% Inputs:
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% -signal: temporal signal to analyse
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% -samplingFreq: sampling frequency of the temporal signal
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% -step_size: how often the power spectrum will be computed in ms
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% -window_size: size of the analysing window in ms
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%
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% Ouput: None
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%
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% author: Guillaume Gibert (guillaume.gibert@ecam.fr)
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% date: 14/03/2023
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%%%%%%%%%%%%%%%%%%%%%%%
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figure;
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subplot(2,1,1);
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t=0:1/samplingFreq:length(signal)/samplingFreq-1/samplingFreq;
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plot(t, signal');
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xlim([0 length(signal)/samplingFreq-1/samplingFreq]);
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ylabel('amplitude (norm. unit)');
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subplot(2,1,2);
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step = fix(step_size*samplingFreq/1000); % one spectral slice every step_size ms
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window = fix(window_size*samplingFreq/1000); % window_size ms data window
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fftn = 2^nextpow2(window); % next highest power of 2
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[S, f, t] = specgram(signal, fftn, samplingFreq, window, window-step);
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S = abs(S(2:fftn*4000/samplingFreq,:)); % magnitude in range 0<f<=4000 Hz.
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S = S/max(S(:)); % normalize magnitude so that max is 0 dB.
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S = max(S, 10^(-40/10)); % clip below -40 dB.
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S = min(S, 10^(-3/10)); % clip above -3 dB.
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imagesc (t, f, log(S)); % display in log scale
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set (gca, "ydir", "normal"); % put the 'y' direction in the correct direction
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xlabel('time (s)');
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ylabel('frequency (Hz)');
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function [power, duration] = frequencySpectrum(signal, fs, pad)
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%%%%%%%%%%%%%%%%%%
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%function power = frequencySpectrum(signal, fs, pad)
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%
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% Task: Display the power spectrum (lin and log scale) of a given signal
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%
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% Input:
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% - signal: the input signal to process
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% - fs: the sampling rate
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% -pad: boolean if true, signal is padded with 0 to the next power of 2 -> FFT instead of DFT
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%
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% Output:
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% - power: the power spectrum
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%
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%
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% Guillaume Gibert, guillaume.gibert@ecam.fr
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% 25/04/2022
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%%%%%%%%%%%%%%%%%%
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n = length(signal); % number of samples
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if (pad)
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n = 2^nextpow2(n);
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end
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tic
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y = fft(signal, n);% compute DFT of input signal
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duration = toc;
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power = abs(y).^2/n; % power of the DFT
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[val, ind] = max(power); % find the mx value of DFT and its index
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if (1)
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% plots
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figure;
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subplot(1,3,1) % time plot
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t=0:1/fs:(n-1)/fs; % time range
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%pad signal with zeros
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if (pad)
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signal = [ signal; zeros( n-length(signal), 1)];
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end
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plot(t, signal)
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xticks(0:0.1*fs:n*fs);
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xticklabels(0:0.1:n/fs);
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xlabel('Time (s)');
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ylabel('Amplitude (a.u.)');
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subplot(1,3,2) % linear frequency plot
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f = (0:n-1)*(fs/n); % frequency range
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plot(f,power, 'b*'); hold on;
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plot(f,power, 'r');
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xlabel('Frequency (Hz)')
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ylabel('Power (a.u.)')
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subplot(1,3,3) % log frequency plot
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plot(f,10*log10(power/power(ind)));
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xlabel('Frequency (Hz)')
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ylabel('Power (dB)')
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end
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function spectrogram(signal, samplingFreq, step_size, window_size)
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%%%%%%%%%%%%%%%%%%%%%%%
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%function spectrogram(signal, samplingFreq, step_size, window_size)
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% ex.: spectrogram(signal, samplingFreq, step_size, window_size)
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%
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% Task: Plot the spectrogram of a given signal
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%
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% Inputs:
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% -signal: temporal signal to analyse
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% -samplingFreq: sampling frequency of the temporal signal
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% -step_size: how often the power spectrum will be computed in ms
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% -window_size: size of the analysing window in ms
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%
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% Ouput: None
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%
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% author: Guillaume Gibert (guillaume.gibert@ecam.fr)
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% date: 14/03/2023
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%%%%%%%%%%%%%%%%%%%%%%%
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figure;
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subplot(2,1,1);
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t=0:1/samplingFreq:length(signal)/samplingFreq-1/samplingFreq;
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plot(t, signal');
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xlim([0 length(signal)/samplingFreq-1/samplingFreq]);
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ylabel('amplitude (norm. unit)');
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subplot(2,1,2);
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step = fix(step_size*samplingFreq/1000); % one spectral slice every step_size ms
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window = fix(window_size*samplingFreq/1000); % window_size ms data window
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fftn = 2^nextpow2(window); % next highest power of 2
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[S, f, t] = specgram(signal, fftn, samplingFreq, window, window-step);
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S = abs(S(2:fftn*4000/samplingFreq,:)); % magnitude in range 0<f<=4000 Hz.
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S = S/max(S(:)); % normalize magnitude so that max is 0 dB.
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S = max(S, 10^(-40/10)); % clip below -40 dB.
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S = min(S, 10^(-3/10)); % clip above -3 dB.
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imagesc (t, f, log(S)); % display in log scale
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set (gca, "ydir", "normal"); % put the 'y' direction in the correct direction
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xlabel('time (s)');
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ylabel('frequency (Hz)');
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@ -1,3 +1,53 @@
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pkg load signal
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int test = 1;
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%load & plot audio file modulator
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%modulator = fullfile('sound', 'modulator22.wav');
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[audio_data sampling_freq]= audioread('modulator22.wav');
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figure;
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plot(audio_data);
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xlabel('Time (s)');
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ylabel('Amplitude');
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title('Modulator22');
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%spectral anlysis
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if (1)
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t = 5;
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%average
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for i=1:t
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%FFT
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[power, duration]=frequencySpectrum(audio_data,sampling_freq,1);
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duration_fft(i) = duration;
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%DFT
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[power, duration]=frequencySpectrum(audio_data,sampling_freq,0);
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duration_dft(i) = duration;
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sum_fft =0;
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sum_dft =0;
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sum_fft = sum_fft + duration_fft(i);
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sum_dft = sum_fft + duration_dft(i);
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endfor
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%estimate the duration of FFT
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average_fft = sum_fft/t
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average_dft = sum_dft/t
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end
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%Compute and display spectrogram
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if(0)
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spectrogram(audio_data,sampling_freq,5,5);
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%spectrogram(audio_data,sampling_freq,30,5);
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wan = audio_data(0.37*sampling_freq:1.17*sampling_freq);
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tu = audio_data(1.24*sampling_freq:1.75*sampling_freq);
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tri = audio_data(1.84*sampling_freq:2.19*sampling_freq);
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frequencySpectrum(wan,sampling_freq,1);
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frequencySpectrum(tu,sampling_freq,1);
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frequencySpectrum(tri,sampling_freq,1);
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end
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