Using Matlab If given a wav file such as speech.wav Write a code that would resa

Question

Using Matlab

If given a wav file such as speech.wav

Write a code that would resample the speech.wav file using the resample function such as one variable like x or y = resample( another variable, 5, 3);

and then be able to plot the original wav file speech.wav and then plot the resampled wav file to comprare to each other

also write the code that would then play the sound of the new resampled wav file but won't play the original wav file

Note: do not use wavread to read the wavfile and instead use audioread like [y,Fs] = audioread('speech.wav');

Explanation / Answer

This program records the voice
function [norm_voice,h] = Voice_Rec(sample_freq)
option = 'n';
option_rec = 'n';
record_len = 1; %Record time length in seconds
%sample_freq = 8192; %Sampling frequency in Hertz
sample_time = sample_freq * record_len;

'Get ready to record your voice'
name = input('Enter the file name you want to save the file with: ','s');
file_name = sprintf('%s.wav',name);
option_rec = input('Press y to record: ','s');
if option_rec=='y'
while option=='n',
input('Press enter when ready to record--> ');
record = wavrecord(sample_time, sample_freq); %Records the input through the sound card to the variable with specified sampling frequency
input('Press enter to listen the recorded voice--> ');
sound(record, sample_freq);
option = input('Press y to save or n to record again: ','s');
end
wavwrite(record, sample_freq, file_name); %Save the recorded data to a file with the specified file name in .wav format
end
[voice_read,FS,NBITS]=wavread(file_name);
norm_voice = normalize(voice_read);
norm_voice = downsmpl(norm_voice, sample_freq);
le=32;
h=daubcqf(le,'min');


function vec = normalize(vec)

temp_vec = vec-mean(vec);
sum_temp_vec = sum(temp_vec.*temp_vec);
sqrt_temp_vec = sqrt(sum_temp_vec);
vec = (1/sqrt_temp_vec)*temp_vec;

function sampled = downsmpl(voice, freq)

x=freq;
y = freq/2;
z=1;
a=1;
sampled=0;
while z<freq,
sampled(a) = sqrt(abs(voice(z)*voice(z+1)));
a=a+1;
z = z+2;
end
sampled = sampled';


function [h_0,h_1] = daubcqf(N,TYPE)
% [h_0,h_1] = daubcqf(N,TYPE);
%
% Function computes the Daubechies' scaling and wavelet filters
% (normalized to sqrt(2)).
%
% Input:
% N : Length of filter (must be even)
% TYPE : Optional parameter that distinguishes the minimum phase,
% maximum phase and mid-phase solutions ('min', 'max', or
% 'mid'). If no argument is specified, the minimum phase
% solution is used.
%
% Output:
% h_0 : Minimal phase Daubechies' scaling filter
% h_1 : Minimal phase Daubechies' wavelet filter
%
% Example:
% N = 4;
% TYPE = 'min';
% [h_0,h_1] = daubcqf(N,TYPE)
% h_0 = 0.4830 0.8365 0.2241 -0.1294
% h_1 = 0.1294 0.2241 -0.8365 0.4830
%
if(nargin < 2),
TYPE = 'min';
end;
if(rem(N,2) ~= 0),
error('No Daubechies filter exists for ODD length');
end;
K = N/2;
a = 1;
p = 1;
q = 1;
h_0 = [1 1];
for j = 1:K-1,
a = -a * 0.25 * (j + K - 1)/j;
h_0 = [0 h_0] + [h_0 0];
p = [0 -p] + [p 0];
p = [0 -p] + [p 0];
q = [0 q 0] + a*p;
end;
q = sort(roots(q));
qt = q(1:K-1);
if TYPE=='mid',
if rem(K,2)==1,
qt = q([1:4:N-2 2:4:N-2]);
else
qt = q([1 4:4:K-1 5:4:K-1 N-3:-4:K N-4:-4:K]);
end;
end;
h_0 = conv(h_0,real(poly(qt)));
h_0 = sqrt(2)*h_0/sum(h_0); %Normalize to sqrt(2);
if(TYPE=='max'),
h_0 = fliplr(h_0);
end;
if(abs(sum(h_0 .^ 2))-1 > 1e-4)
error('Numerically unstable for this value of "N".');
end;
h_1 = rot90(h_0,2);
h_1(1:2:N)=-h_1(1:2:N);

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