Undefined function 'VAD' for input arguments of type 'double'.
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maheesha madhubashini
el 20 de Mayo de 2017
Respondida: Walter Roberson
el 20 de Mayo de 2017
I have use following downloaded code for convert speech to text.
% % traning phase
clc; clear;close all
w = warning ('off','all');
Fs=8000;
% % For the word "ONE"
filepart1='myrecordone';
filepart2='.wav';
% % check for signal length
% % we will append zeros after VAD to make sure all the signals are of
% % equal length
% % We need same number of MFCC of each signal
length_all_sig=[];
for i=1:10
filename=strcat(filepart1,num2str(i),filepart2);
y1=wavread(filename);
results = VAD(y1,0.1,0.025,0.0125,20,1);
ind_st=(0:size(results)-1)*200+1;
ind_en=(1:size(results))*200;
ind1=ind_st(logical(results));
ind2=ind_en(logical(results));
all_ind=cell2mat(arrayfun(@colon,ind1,ind2,'uni',0));
filt_signal=y1(all_ind);
length_all_sig=[length_all_sig length(filt_signal)];
end
max_length=max(length_all_sig);
all_data_one=[];
for i = 1:10
filename=strcat(filepart1,num2str(i),filepart2);
y1=wavread(filename);
results = VAD(y1,0.1,0.025,0.0125,20,1);
ind_st=(0:size(results)-1)*200+1;
ind_en=(1:size(results))*200;
ind1=ind_st(logical(results));
ind2=ind_en(logical(results));
all_ind=cell2mat(arrayfun(@colon,ind1,ind2,'uni',0));
filt_signal=y1(all_ind);
if length(filt_signal)==max_length
[cepstra1,aspectrum,pspectrum] = melfcc(y1,Fs,'wintime',0.025,'hoptime',0.010);
else
filt_signal=[filt_signal' zeros(1,max_length-length(filt_signal))];
[cepstra1,aspectrum,pspectrum] = melfcc(filt_signal,Fs,'wintime',0.025,'hoptime',0.010);
end
all_data_one=[all_data_one cepstra1];
end
% % For the word "TWO"
all_data_two=[];
filepart1='myrecordtwo';
length_all_sig=[];
for i=1:10
filename=strcat(filepart1,num2str(i),filepart2);
y1=wavread(filename);
results = VAD(y1,0.1,0.025,0.0125,20,1);
ind_st=(0:size(results)-1)*200+1;
ind_en=(1:size(results))*200;
ind1=ind_st(logical(results));
ind2=ind_en(logical(results));
all_ind=cell2mat(arrayfun(@colon,ind1,ind2,'uni',0));
filt_signal=y1(all_ind);
length_all_sig=[length_all_sig length(filt_signal)];
end
max_length=max(length_all_sig);
for i = 1:10
filename=strcat(filepart1,num2str(i),filepart2);
y1=wavread(filename);
results = VAD(y1,0.1,0.025,0.0125,20,1);
ind_st=(0:size(results)-1)*200+1;
ind_en=(1:size(results))*200;
ind1=ind_st(logical(results));
ind2=ind_en(logical(results));
all_ind=cell2mat(arrayfun(@colon,ind1,ind2,'uni',0));
filt_signal=y1(all_ind);
if length(filt_signal)==max_length
[cepstra2,aspectrum,pspectrum] = melfcc(y1,Fs,'wintime',0.025,'hoptime',0.010);
else
filt_signal=[filt_signal' zeros(1,max_length-length(filt_signal))];
[cepstra2,aspectrum,pspectrum] = melfcc(filt_signal,Fs,'wintime',0.025,'hoptime',0.010);
end
all_data_two=[all_data_two cepstra2];
end
% % For the word "THREE"
all_data_three=[];
filepart1='myrecordthree';
length_all_sig=[];
for i=1:10
filename=strcat(filepart1,num2str(i),filepart2);
y1=wavread(filename);
results = VAD(y1,0.1,0.025,0.0125,20,1);
ind_st=(0:size(results)-1)*200+1;
ind_en=(1:size(results))*200;
ind1=ind_st(logical(results));
ind2=ind_en(logical(results));
all_ind=cell2mat(arrayfun(@colon,ind1,ind2,'uni',0));
filt_signal=y1(all_ind);
length_all_sig=[length_all_sig length(filt_signal)];
end
max_length=max(length_all_sig);
for i = 1:10
filename=strcat(filepart1,num2str(i),filepart2);
y1=wavread(filename);
results = VAD(y1,0.1,0.025,0.0125,20,1);
ind_st=(0:size(results)-1)*200+1;
ind_en=(1:size(results))*200;
ind1=ind_st(logical(results));
ind2=ind_en(logical(results));
all_ind=cell2mat(arrayfun(@colon,ind1,ind2,'uni',0));
filt_signal=y1(all_ind);
if length(filt_signal)==max_length
[cepstra3,aspectrum,pspectrum] = melfcc(y1,Fs,'wintime',0.025,'hoptime',0.010);
else
filt_signal=[filt_signal' zeros(1,max_length-length(filt_signal))];
[cepstra3,aspectrum,pspectrum] = melfcc(filt_signal,Fs,'wintime',0.025,'hoptime',0.010);
end
all_data_three=[all_data_three cepstra3];
end
% % Building model
X=[all_data_one'];
options = statset('MaxIter',500,'Display','final');
obj1 = gmdistribution.fit(X,8,'CovType',...
'diagonal','Options',options);
X=[all_data_two'];
obj2 = gmdistribution.fit(X,8,'CovType',...
'diagonal','Options',options);
X=[all_data_three'];
obj3 = gmdistribution.fit(X,8,'CovType',...
'diagonal','Options',options);
% % Test data
test_data=cepstra1';
% test_data=cepstra1';
% test_data=cepstra2';
% % Word recognition
[~,nlogl1] = posterior(obj1,test_data);
[~,nlogl2] = posterior(obj2,test_data);
[~,nlogl3] = posterior(obj3,test_data);
log_like=[nlogl1 nlogl2 nlogl3];
[~,Spoken_word]=min(log_like)
but it gives
Error in main4 (line 26)
results = VAD(y1,0.1,0.025,0.0125,20,1);
what should I do for this
1 comentario
Image Analyst
el 20 de Mayo de 2017
Did you write VAD yourself? If not, do you know where it's located on your computer? If not, then why do you think MATLAB should know anything at all about this function?
Respuestas (1)
Walter Roberson
el 20 de Mayo de 2017
"You need a toolbox from http://www.ee.columbia.edu/~dpwe/resources/matlab/rastamat/ to run my files.
Get the VAD program from Bowon Lee"
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