Can you help us debug and fix this code entirely?
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%on line sound importing or recourding
recObj = audiorecorder;
recordblocking(recObj, 15);
play(recObj);
y = getaudiodata(recObj);
plot(y);
play(recObj);
y = getaudiodata(recObj);
plot(y);
%code of AEC
M=4001;
fs=8000;
[B,A]=cheby2(4,20,[0.1, 0.7]);
Hd=dfilt.df2t([zeros(1,6) B]);
hFVT=fvtool(Hd);
set(hFVT, 'color' ,[1 1 1])
v=340;
H = filter(Hd,log(0.99*rand(1,M)+0.01).* ...
sign (randn(1,M)).*exp(-0.002*(1:M)));
H = H/norm(H)*4; % Room Impulse Response
plot(0:1/fs:0.5,H);
xlabel('Time [sec]' );
ylabel('Amplitude' );
title( 'Room Impulse Response' );
set(gcf, 'color' , [1 1 1])
figure(1)
hold on
load nearspeech
n = 1: length (v);
t=n/fs;
plot(t,v);
axis([0 33.5 -1 1]);
xlabel('Time [sec]' );
ylabel('Amplitude' );
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title('Near-end speech signal' );
set(gcf, 'color' , [1 1 1])
figure(2)
hold on
load farspeech
x =x( 1: length (x));
dhat = filter(H,1,x);
plot(t,dhat);
axis([0 33.5 -1 1]);xlabel('Time [sec]' );
ylabel('Amplitude' );
title('Far-End speech Signal' );
set(gcf, 'color' , [1 1 1])
figure(3)
hold on
d=dhat + v+0.001*randn(length(v),1);
plot(t,d);
axis([0 33.5 -1 1]);
xlabel('Time [sec]' );
ylabel('Amplitude' );
title('Microphon Signal' );
set(gcf, 'color' , [1 1 1])
figure(4)
hold on
mu=0.025;
W0 = zeros(1,2048);
del = 0.01;
lam = 0.98;
x = x(1:length(W0)*floor(length(x)/length(W0)));
d = d(1:length(W0)*floor(length(d)/length(W0)));
% Construct the Frequency-Domain Adaptive Filter
fdafilt = dsp.FrequencyDomainAdaptiveFilter('Length',32,'StepSize',mu);
[y,e] = fdafilt(x,d);
n = 1:length(e);
t = n/fs;
pos = get(gcf,'Position');
set(gcf,'Position',[pos(1), pos(2)-100,pos(3),(pos(4)+111)])
subplot(3,1,1);
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plot(t,v(n),'g');
([0 33.5 -1 1]);
xlabel('Time [sec]');
ylabel('Amplitude');
title('Near-End Speech Signal of MR.ABERA');
subplot(3,1,2);
plot(t,d(n),'b');
axis([0 33.5 -1 1]);
ylabel('Amplitude');
title('Microphone Signal Mr. Amex + Mr.Abera');
subplot(3,1,3);
plot(t,v(n),'r');
axis([0 33.5 -1 1]);
ylabel('Amplitude');axis
title('Output of Acoustic Echo Canceller');
set(gcf, 'color' , [1 1 1])
#%Normalized LMS method
FrameSize = 102; NIter = 14;
lmsfilt2 = dsp.LMSFilter('Length',11,'Method','Normalized LMS', ...
'StepSize',0.005);
firfilt2 = dsp.FIRFilter('Numerator', fir1(10,[.05, .075]));
sinewave = dsp.SineWave('Frequency',0.001, ...
'SampleRate',1,'SamplesPerFrame',FrameSize);
TS = dsp.TimeScope('TimeSpan',FrameSize*NIter,'TimeUnits','Seconds',...
'YLimits',[-3 3],'BufferLength',2*FrameSize*NIter, ...
'ShowLegend',true,'ChannelNames', ...
{'echo signal', 'Filtered signal'});
%%
% Pass the echo input signal into the LMS filter and view the filtered
% output in the time scope.
for k = 1:NIter
x = randn(FrameSize,1);
% Input signal
d = firfilt2(x) + sinewave(); % echo + Signal
[y,e,w] = lmsfilt2(x,d);
TS([d,e]);
% echo = channel 1; Filtered = channel 2
end
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#% convergence performance of regular NLMS
x = 0.1*randn(500,1);
[b,err,res] = fircband(12,[0 0.4 0.5 1], [1 1 0 0], [1 0.2],...
{'w' 'c'});
d = filter(b,1,x);
lms_normalized = dsp.LMSFilter(13,'StepSize',mu,...
'Method','Normalized LMS','WeightsOutputPort',true);
[~,e1,~] = lms_normalized(x,d);
plot([e1]);
title('NLMS Conversion Performance');
legend('NLMS Derived Filter Weights');
#% convergence performance of regular LMS
x = 0.1*randn(500,1);
[b,err,res] = fircband(12,[0 0.4 0.5 1], [1 1 0 0], [1 0.2],...
{'w' 'c'});
d = filter(b,1,x);
lms_normalized = dsp.LMSFilter(13,'StepSize',mu,...
'Method','LMS','WeightsOutputPort',true);
[~,e2,~] = lms_normalized(x,d);
plot([e2]);
title('LMS Conversion Performance');
legend('LMS Derived Filter Weights');
#% comparing the LMS and NLMS convergence performance
x = 0.1*randn(500,1);
[b,err,res] = fircband(12,[0 0.4 0.5 1], [1 1 0 0], [1 0.2],...
{'w' 'c'});
d = filter(b,1,x);
lms = dsp.LMSFilter(13,'StepSize',mu,'Method',...
'Normalized LMS','WeightsOutputPort',true);
lms_normalized = dsp.LMSFilter(13,'StepSize',mu,...
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'Method','Normalized LMS','WeightsOutputPort',true);
lms_nonnormalized = dsp.LMSFilter(13,'StepSize',mu,...
'Method','LMS','WeightsOutputPort',true);
[~,e1,~] = lms_normalized(x,d);
[~,e2,~] = lms_nonnormalized(x,d);
plot([e1,e2]);
title('Comparing the LMS and NLMS Conversion Performance');
legend('NLMS Derived Filter Weights', ...
'LMS Derived Filter Weights','Location', 'NorthEast');
main issue we keep facing is
Error using load
Unable to find file or directory 'nearspeech'.
Error in OG (line 30)
load nearspeech
0 Comments
Answers (1)
Walter Roberson
on 18 May 2025
You can get nearspeech.mat and farspeech.mat as part of the example
openExample('audio/AcousticEchoCancellationAecExample')
5 Comments
Walter Roberson
on 18 May 2025
I have no reason to doubt the correctness of the code from https://www.scribd.com/document/563550610/project-paper
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