Can you help us debug and fix this code entirely?

4 views (last 30 days)
%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' );
25
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);
26
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
27
#% 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,...
28
'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

Answers (1)

Walter Roberson
Walter Roberson on 18 May 2025
You can get nearspeech.mat and farspeech.mat as part of the example
openExample('audio/AcousticEchoCancellationAecExample')
  5 Comments
Barnabas
Barnabas on 18 May 2025
i can provide. @Bernabas is my handle on telegram. if youre willing and got spare time.

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