Hello;
>
>I was wondering if anyone would be willing to share or direct me towards some
Java or C code on how to convert from Linear Prediction Coefficients to Line
Spectral Frequencies and vice versa.
>
>I am able to generate the LP coefficients using the Levinson algorithm, but am
looking for some help to get to LS frequencies.
>Thanks.
>
>Regards,
>Ray
hi,
This code provided in matlad
function lsf = poly2lsf(a)
%POLY2LSF Prediction polynomial to line spectral frequencies.
% LSF = POLY2LSF(A) converts the prediction polynomial specified by A,
% into the corresponding line spectral frequencies, LSF.
%
% POLY2LSF normalizes the prediction polynomial by A(1).
%
% See also LSF2POLY, POLY2RC, POLY2AC, RC2IS.
% Author(s): A.Ramasubramanian
% Copyright 1988-2002 The MathWorks, Inc.
% $Revision: 1.7 $ $Date: 2002/04/15 01:15:43 $
%
% Reference:
% A.M. Kondoz, "Digital Speech: Coding for Low Bit Rate Communications
% Systems" John Wiley & Sons 1994, Chapter 4.
a = a(:);
if ~isreal(a),
error('Line spectral frequencies are not defined for complex
polynomials.');
end
% Normalize the polynomial if a(1) is not unity
if a(1) ~= 1.0,
a = a./a(1);
end
if (max(abs(roots(a))) >= 1.0),
error('The polynomial must have all roots inside of the unit
circle.');
end
% Form the sum and differnce filters
p = length(a)-1; % The leading one in the polynomial is not used
a1 = [a;0];
a2 = a1(end:-1:1);
P1 = a1-a2; % Difference filter
Q1 = a1+a2; % Sum Filter
% If order is even, remove the known root at z = 1 for P1 and z = -1 for Q1
% If odd, remove both the roots from P1
if rem(p,2), % Odd order
P = deconv(P1,[1 0 -1]);
Q = Q1;
else % Even order
P = deconv(P1,[1 -1]);
Q = deconv(Q1,[1 1]);
end
rP = roots(P);
rQ = roots(Q);
aP = angle(rP(1:2:end));
aQ = angle(rQ(1:2:end));
lsf = sort([aP;aQ]);
% [EOF] poly2lsf.m
can you help me to solve this problem?
I need log spectral distortion formula between quantized LPC and original LPC.