Matlab Code to plot Sampling rate or frequency

The original “abracadabras” signals at 44100Hz sampling frequency.

Compute spectrum of abracadabras for sampling frequency at 44100Hz. 

 

Perform  the average of 10 abracadabras and then plot the spectrum of 10 abracadabras for sampling frequency at 44100Hz

 

Perform average spectrum of 10 abracadabras

Re-record, sample at 8 KHz.

 

Compute spectrum of abracadabras for sample frequency 8Khz

Matlab code

%Minh Anh Nguyen

%ECE/BIOM 537 Biomedical Signal Processing, Colorado State University

%Email: minhanhnguyen@q.com

%Homework 5

close all;

clc;

figure;

%Read in the sound

%returns the sample rate(FS) in Hertz

%N = number sample

%the number of bits per sample (BITS) used to encode the data in the file

ax(1)= subplot (3,2,1);

%myvoice1 = audioread('J:\BIOM_Signal_processing\HW2\Aka1_a.wma');

%[y1, fs1] = audioread('J:\BIOM_Signal_processing\HW2\Aka1_a.wma');

myvoice1 = audioread('J:\BIOM_Signal_processing\HW2\Aka1_a.wma');

[y1, fs1] = audioread('J:\BIOM_Signal_processing\HW2\Aka1_a.wma');

N = length(myvoice1); 

%%player=audioplayer(y1,N); play(player)

t1 = (0:1:N-1)/fs1;

plot(t1, myvoice1);

title ('My voice [Abrakakabra]#1 Number of sample 229364')

xlabel('time (sec)');

ylabel(' signal strength')

axis tight

grid on;

ax(2)=subplot (3,2,2);

myvoice2 = audioread('J:\BIOM_Signal_processing\HW2\ala_2.wma');

[y2, fs2] = audioread('J:\BIOM_Signal_processing\HW2\ala_2.wma');

N2 = length(myvoice2);

t2 = (0:1:length(myvoice2)-1)/fs2;

plot(t2, myvoice2);

title ('My voice [repeat Abrakakabra]#2 Number sample 370661')

xlabel('time (sec)');

ylabel(' signal strength')

axis tight

grid on;

ax(3)=subplot (3,2,3);

myvoice3 = audioread('J:\BIOM_Signal_processing\HW2\alka3.wma');

[y3, fs3] = audioread('J:\BIOM_Signal_processing\HW2\alka3.wma');

N3 = length(myvoice3);

t3 = (0:1:length(myvoice3)-1)/fs3;

plot(t3, myvoice3);

title ('My voice [repeat Abrakakabra]#3 number of sample 376790')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

ax(4)= subplot (3,2,4);

myvoice4 = audioread('J:\BIOM_Signal_processing\HW2\Alka_4.wma');

[y4, fs4] = audioread('J:\BIOM_Signal_processing\HW2\Alka_4.wma');

N4 = length(myvoice4);

t4 = (0:1:length(myvoice4)-1)/fs4;

plot(t4, myvoice4);

title ('My voice [repeat Abrakakabra]#4 Number of sample 247798')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

ax(5)= subplot (3,2,5);

myvoice5 = audioread('J:\BIOM_Signal_processing\HW2\Alka_5.wma');

[y5, fs5]= audioread('J:\BIOM_Signal_processing\HW2\Alka_5.wma');

N5 = length(myvoice5);

t5 = (0:1:length(myvoice5)-1)/fs5;

plot(t5, myvoice5);

title ('My voice [repeat Abrakakabra]#5 number of sample 266232')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

ax(5)= subplot (3,2,6);

%ax(6)= subplot (2,2,1);

myvoice6 = audioread('J:\BIOM_Signal_processing\HW2\Aka_6.wma');

[y6, fs6] = audioread('J:\BIOM_Signal_processing\HW2\Aka_6.wma');

N6 = length(myvoice6);

t6 = (0:1:length(myvoice6)-1)/fs6;

plot(t6, myvoice6);

title ('My voice [repeat Abrakakabra]#6 number of sample 241624')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

figure;

ax(7)=subplot (2,2,1);

myvoice7 = audioread('J:\BIOM_Signal_processing\HW2\alk_7.wma');

[y7, fs7] = audioread('J:\BIOM_Signal_processing\HW2\alk_7.wma');

N7 = length(myvoice7);

t7 = (0:1:length(myvoice7)-1)/fs7;

plot(t7, myvoice7);

title ('My voice [repeat Abrakakabra]#7 number of sample 303099')

xlabel('time (sec)');

ylabel('signal strength')  

axis tight

grid on;

ax(8)=subplot (2,2,2);

myvoice8 = audioread('J:\BIOM_Signal_processing\HW2\alk8.wma');

[y8, fs8] = audioread('J:\BIOM_Signal_processing\HW2\alk8.wma');

N8 = length(myvoice8);

t8 = (0:1:length(myvoice8)-1)/fs8;

plot(t8, myvoice8);

title ('My voice [repeat Abrakakabra]#8 number of sample 270333 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%figure;

ax(8)=subplot (2,2,3);

myvoice9 = audioread('J:\BIOM_Signal_processing\HW2\ala_9.wma');

[y9, fs9] = audioread('J:\BIOM_Signal_processing\HW2\ala_9.wma');

N9 = length(myvoice9);

t9 = (0:1:length(myvoice9)-1)/fs9;

plot(t9, myvoice9);

title ('My voice [repeat Abrakakabra]#9 number of sample 206829 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%figure;

ax(9)=subplot (2,2,4);

myvoice10 = audioread('J:\BIOM_Signal_processing\HW2\aka_10.wma');

[y10, fs10] = audioread('J:\BIOM_Signal_processing\HW2\aka_10.wma');

N10 = length(myvoice10);

t10 = (0:1:length(myvoice10)-1)/fs10;

plot(t10, myvoice10);

title ('My voice [repeat Abrakakabra]#10 number of sample 169961 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%Compute the power spectral density, a measurement of the energy at various frequencies

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N);

Y = fft(y1, NFFT) / N;

f = (fs1 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

ax(10)= subplot (4,2,1);

plot (f, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#1 Number of sample 229364')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N2);

Y2 = fft(y2, NFFT) / N2;

f2 = (fs2 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y2(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(11)= subplot (4,2,2);

plot (f2, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#2 Number of sample 370661')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N3);

Y3 = fft(y3, NFFT) / N3;

f3 = (fs3 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y3(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(12)= subplot (4,2,3);

plot (f3, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#3 Number of sample 376790')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N4);

Y4 = fft(y4, NFFT) / N4;

f4 = (fs4 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y4(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(13)= subplot (4,2,4);

plot (f4, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#4 Number of sample 247798')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N5);

Y5 = fft(y5, NFFT) / N5;

f5 = (fs5 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y5(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(14)= subplot (4,2,5);

plot (f5, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#5 Number of sample 266232')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N6);

Y6 = fft(y6, NFFT) / N6;

f6 = (fs6 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y6(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(16)= subplot (4,2,6);

plot (f6, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#6 Number of sample 241624')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

figure;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N7);

Y7 = fft(y7, NFFT) / N7;

f7 = (fs7 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y7(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(17)= subplot (5,2,1);

plot (f7, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#7 Number of sample 303099')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N8);

Y8 = fft(y8, NFFT) / N8;

f8 = (fs8 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y8(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(18)= subplot (5,2,2);

plot (f8, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#8 Number of sample 270333')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N9);

Y9 = fft(y9, NFFT) / N9;

f9 = (fs9 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y9(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(19)= subplot (5,2,3);

plot (f9, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#9 Number of sample 206829')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(N10);

Y10 = fft(y10, NFFT) / N10;

f10 = (fs10 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(Y10(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

ax(20)= subplot (5,2,4);

plot (f10, amp);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#10 Number of sample 169961')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

figure;

%subplot (6,2,1);

%%%Average spectrum of 10 abracadabras

X1 = fft(y1);

X1 = X1(1:length(X1)/2+1); % One-sided DFT

P = (abs(X1)/length(y1)).^2;     % Compute the mean-square power

P(2:end-1) = 2*P(2:end-1); % Factor of two for one-sided estimate

% at all frequencies except zero and the Nyquist

Hmss = dspdata.msspectrum(P,'Fs',fs1,'spectrumtype','onesided');

plot(Hmss)          % Plot the mean-square spectrum.

figure;

%subplot (6,2,1);

%%%Average spectrum of 10 abracadabras

X1_2 = fft(y2);

X1_2 = X1_2(1:length(X1)/2+1); % One-sided DFT

P = (abs(X1_2)/length(y2)).^2;     % Compute the mean-square power

P(2:end-1) = 2*P(2:end-1); % Factor of two for one-sided estimate

% at all frequencies except zero and the Nyquist

Hmss = dspdata.msspectrum(P,'Fs',fs1,'spectrumtype','onesided');

plot(Hmss)          % Plot the mean-square spectrum.

%(i) Using the program of your choice, average your 10 "abracadabras" from your previous %assignment, and plot the result. Be sure to line up the signals prior to the averaging operation. %Submit your code with your plot.

%% line up the signals prior to the averaging operation

y2new = y2(:,1);   %% create signal in 1D

y1new = y1(:,1);   %% signal 1

y3new = y3(:,1);   %% create signal in 1D

y4new = y4(:,1);   %% create signal in 1D

y5new = y5(:,1);   %% create signal in 1D

y6new = y6(:,1);   %% create signal in 1D

y7new = y7(:,1);   %% create signal in 1D

y8new = y8(:,1);   %% create signal in 1D

y9new = y9(:,1);   %% create signal in 1D

y10new =y10(:,1);  %% create signal in 1D

%time average of 1 “abracadabra” with ensemble average of all.

vshift1 = circshift (y1new, 20333);

vshift2 = circshift (y2new, -41806);

vshift3 = circshift (y3new, 20333);

vshift4 = circshift (y4new, 20333);

vshift5 = circshift (y5new, 20333);

vshift6 = circshift (y6new, 20333);

vshift7 = circshift (y7new, 20333);

vshift8 = circshift (y8new, 20333);

vshift9 = circshift (y9new, 20333);

%vshift10 = circshift (y10new, 20333);

vshiftcut1 = vshift1(1: 169961);

vshiftcut2 = vshift2(1: 169961);

vshiftcut3 = vshift3(1: 169961);

vshiftcut4 = vshift4(1: 169961);

vshiftcut5 = vshift5(1: 169961);

vshiftcut6 = vshift6(1: 169961);

vshiftcut7 = vshift7(1: 169961);

vshiftcut8 = vshift8(1: 169961);

vshiftcut9 = vshift9(1: 169961);

S = [vshiftcut1(:), vshiftcut2(:), vshiftcut3(:), vshiftcut4(:), vshiftcut5(:), vshiftcut6(:), vshiftcut7(:), vshiftcut8(:), vshiftcut9(:), y10new(:)];

MeanS = mean(S');

figure,

plot (MeanS);

title ('ensemble average of all  my voice [repeat Abrakakabra]')

xlabel('time (sec)');

ylabel('signal strength');

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(S));

YS = fft(S, NFFT) / length(S);

fS = (fs10 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp = ( 2 * abs(YS(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure,

plot (fS, amp);

title ('plot single-sided amplitude spectrume of average 10 [Abrakakabra]')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

 % Plot the mean-square spectrum.        

figure;

%subplot (6,2,1);

%%%Average spectrum of 10 abracadabras

XS = fft(S);

XS = XS(1:length(XS)/2+1); % One-sided DFT

P = (abs(XS)/length(S)).^2;     % Compute the mean-square power

P(2:end-1) = 2*P(2:end-1); % Factor of two for one-sided estimate

% at all frequencies except zero and the Nyquist

Hmss = dspdata.msspectrum(P,'Fs',fs1,'spectrumtype','onesided');

plot(Hmss)          % Plot the mean-square spectrum.

 %calculate the StDev:

StdS = std(S');

fsorg=44100;

fs = 8000;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_1 = resample(y1,fs,fsorg);

N1_1 = length(y_1);

t1_1 = (0:1:length(y_1)-1)/fs;

plot(t1_1, y_1);

title ('Abrakakabra #1 for 8Khz, number of sample 41608 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_2 = resample(y2,fs,fsorg);

N1_2 = length(y_2);

t1_2 = (0:1:length(y_2)-1)/fs;

plot(t1_2, y_2);

title ('Abrakakabra #2 for 8Khz, number of sample 67241 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_3 = resample(y3,fs,fsorg);

N1_3 = length(y_3);

t1_3 = (0:1:length(y_3)-1)/fs;

plot(t1_3, y_3);

title ('Abrakakabra #3 for 8Khz, number of sample 68352 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_4 = resample(y4,fs,fsorg);

N1_4 = length(y_4);

t1_4 = (0:1:length(y_4)-1)/fs;

plot(t1_4, y_4);

title ('Abrakakabra #4 for 8Khz, number of sample 44953 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_5 = resample(y5,fs,fsorg);

N1_5 = length(y_5);

t1_5 = (0:1:length(y_5)-1)/fs;

plot(t1_5, y_5);

title ('Abrakakabra #5 for 8Khz, number of sample 48297 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_6 = resample(y6,fs,fsorg);

N1_6 = length(y_6);

t1_6 = (0:1:length(y_6)-1)/fs;

plot(t1_6, y_6);

title ('Abrakakabra #6 for 8Khz, number of sample 43833 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_7 = resample(y7,fs,fsorg);

N1_7 = length(y_7);

t1_7 = (0:1:length(y_7)-1)/fs;

plot(t1_7, y_7);

title ('Abrakakabra #7 for 8Khz, number of sample 54984 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_8 = resample(y8,fs,fsorg);

N1_8 = length(y_8);

t1_8 = (0:1:length(y_8)-1)/fs;

plot(t1_8, y_8);

title ('Abrakakabra #8 for 8Khz, number of sample 49040 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_9 = resample(y9,fs,fsorg);

N1_9 = length(y_9);

t1_9 = (0:1:length(y_9)-1)/fs;

plot(t1_9, y_9);

title ('Abrakakabra #9 for 8Khz, number of sample 37520 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%  resample is your function. To downsample signal from 44100 Hz to 8000 Hz:

%(the "1" and "2" arguments define the resampling ratio: 8000/44100 = 1/2)

%To upsample back to 44100 Hz: x2 = resample(y,2,1);

figure;

y_10 = resample(y10,fs,fsorg);

N1_10 = length(y_10);

t1_10 = (0:1:length(y_10)-1)/fs;

plot(t1_10, y_10);

title ('Abrakakabra #10 for 8Khz, number of sample 30832 ')

xlabel('time (sec)');

ylabel('signal strength')

axis tight

grid on;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%Compute the power spectral density, a measurement of the energy at various frequencies

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_1));

Y_1 = fft(y_1, NFFT) / length (y_1);

f_1 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_1 = ( 2 * abs(Y_1(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_1, amp_1);

title ('plot single-sided amplitude spectrume of Abrakakabra #1 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_2));

Y_2 = fft(y_2, NFFT) / length(y_2);

f_2 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_2 = ( 2 * abs(Y_2(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_2, amp_2);

title ('plot single-sided amplitude spectrume of [Abrakakabra]#2 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_3));

Y_3 = fft(y_3, NFFT) / length(y_3);

f_3 = (fs3 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_3 = ( 2 * abs(Y3(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_3, amp_3);

title ('plot single-sided amplitude spectrume of [Abrakakabra]#3 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_4));

Y_4 = fft(y_4, NFFT) / length(y_4);

f_4 = (fs4 / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_4 = ( 2 * abs(Y_4(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_4, amp_4);

title ('plot single-sided amplitude spectrume of  [Abrakakabra]#4 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

figure;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_5));

Y_5 = fft(y_5, NFFT) / length(y_5);

f_5 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_5 = ( 2 * abs(Y_5(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

plot (f_5, amp_5);

title ('plot single-sided amplitude spectrume of [Abrakakabra]#5 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_6));

Y_6 = fft(y_6, NFFT) / length(y_6);

f_6 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_6 = ( 2 * abs(Y_6(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

 figure;

plot (f_6, amp_6);

title ('plot single-sided amplitude spectrume of  [Abrakakabra]#6 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

figure;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_7));

Y_7 = fft(y_7, NFFT) /length(y_7);

f_7 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_7 = ( 2 * abs(Y_7(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

plot (f_7, amp_7);

title ('plot single-sided amplitude spectrume of  [Abrakakabra]#7 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_8));

Y_8 = fft(y_8, NFFT) / length(y_8);

f_8 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_8 = ( 2 * abs(Y_8(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_8, amp_8);

title ('plot single-sided amplitude spectrume of [Abrakakabra]#8 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_9));

Y_9 = fft(y_9, NFFT) / length(y_9);

f_9 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_9 = ( 2 * abs(Y_9(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_9, amp_9);

title ('plot single-sided amplitude spectrume of my voice [Abrakakabra]#9 Number of sample 206829')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;

%%%  DFT to describe the signal in the frequency

NFFT = 2 ^ nextpow2(length(y_10));

Y_10 = fft(y_10, NFFT) / length(y_10);

f_10 = (fs / 2 * linspace(0, 1, NFFT / 2+1))'; % Vector containing frequencies in Hz

amp_10 = ( 2 * abs(Y_10(1: NFFT / 2+1))); % Vector containing corresponding amplitudes

figure;

plot (f_10, amp_10);

title ('plot single-sided amplitude spectrume of  [Abrakakabra]#10 at 8Khz')

xlabel ('frequency (Hz)')

ylabel ('|y(f)|')

grid on;