Code covered by the BSD License
 Callbacks_formant_estimat...SENSE COMPUTER AND SET FILE DELIMITER
 [A,G,a,r]=autolpc(x,p)
% function to computer the autocorrelation method solution
 [Fmc,startsav,endsav]=ext...% function to extend regions of formant runs based on adjacent frames
 [nrun,startsav,endsav]=ru...% function to find runs (of at least length 5 frames) of stable formants
 d123=dist123(F1,F2)
% function to compute distance between two formant vectors, each with three
 d12=dist12(F1,F2)
% function to compute distance between two formant vectors, each with two
 d23=dist23(F1,F2)
% function to compute distance between two formant vectors, each with two
 formant_estimation_GUI25
Modifiable runGUI file
 pathnew_matlab_central.mpathnew_matlab_central

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Formant Estimation
by
Speech Processing
30 Jan 2014
(Updated
18 Apr 2014)
Illustrates an algorithm for estimating the locations of the formants of voiced speech intervals

[A,G,a,r]=autolpc(x,p)

function [A,G,a,r]=autolpc(x,p)
%
% function to computer the autocorrelation method solution
%
% Inputs:
% x is the signal frame (usually speech weighted by a window)
% p is the lpc model order
%
% Outputs:
% A is the denominator vector for the lpc solution, i.e.,
% A=1a1z^{1}a2z^{2}...apz^{p}
% G is the lpc model gain (rms prediction error)
% a is the lpc polynomial (without the 1 term)
% r is the vector of autocorrelation coefficients
% see also ATOK, KTOA, RTOA
% solve for the lpc polynomial using a simple matrix inversion method
L=length(x);
r=[];
for i=0:p
r=[r; sum(x(1:Li).*x(1+i:L))];
end
R=toeplitz(r(1:p));
a=inv(R)*r(2:p+1);
A=[1; a];
G=sqrt(sum(A.*r));
end


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