Dawn@4: function [H1H2, H2H4] = func_GetH1H2_H2H4(H1, H2, H4, Fs, F0, F1, F2, B1, B2)
Dawn@4: % [H1H2, H2H4] = func_GetH1H2_H2H4(H1, H2, H4, Fs, F0, F1, F2, B1, B2)
Dawn@4: % Input:  H1, H2, H4, vectors
Dawn@4: %         Fs - sampling frequency
Dawn@4: %         F0 - vector of fundamental frequencies
Dawn@4: %         Fx, Bx - vectors of formant frequencies and bandwidths
Dawn@4: % Output: H1A1, H1A2, H1A3 vectors
Dawn@4: % Notes:  Function produces the corrected versions of the parameters. They
Dawn@4: % are stored as HxHx for compatibility reasons. Use func_buildMData.m to
Dawn@4: % recreate the mat data with the proper variable names.
Dawn@4: % Also note that the bandwidths from the formant trackers are not currently
Dawn@4: % used due to the variability of those measurements.
Dawn@4: %
Dawn@4: % Author: Yen-Liang Shue, Speech Processing and Auditory Perception Laboratory, UCLA
Dawn@4: % Copyright UCLA SPAPL 2009
Dawn@4: 
Dawn@4: 
Dawn@4: if (nargin == 7)
Dawn@4:   B1 = func_getBWfromFMT(F1, F0, 'hm');
Dawn@4:   B2 = func_getBWfromFMT(F2, F0, 'hm');
Dawn@4: end
Dawn@4: 
Dawn@4: 
Dawn@4: H1_corr = H1 - func_correct_iseli_z(F0, F1, B1, Fs);
Dawn@4: H1_corr = H1_corr - func_correct_iseli_z(F0, F2, B2, Fs);
Dawn@4: H2_corr = H2 - func_correct_iseli_z(2*F0, F1, B1, Fs);
Dawn@4: H2_corr = H2_corr - func_correct_iseli_z(2*F0, F2, B2, Fs);
Dawn@4: H4_corr = H4 - func_correct_iseli_z(4*F0, F1, B1, Fs);
Dawn@4: H4_corr = H4_corr - func_correct_iseli_z(4*F0, F2, B2, Fs);
Dawn@4: 
Dawn@4: H1H2 = H1_corr - H2_corr;
Dawn@4: H2H4 = H2_corr - H4_corr;
Dawn@4: 
Dawn@4: 
Dawn@4: