Mercurial > hg > emotion-detection-top-level
comparison Code/Descriptors/Matlab/MPEG7/FromWeb/VoiceSauce/func_GetH1H2_H2H4.m @ 4:92ca03a8fa99 tip
Update to ICASSP 2013 benchmark
author | Dawn Black |
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date | Wed, 13 Feb 2013 11:02:39 +0000 |
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3:e1cfa7765647 | 4:92ca03a8fa99 |
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1 function [H1H2, H2H4] = func_GetH1H2_H2H4(H1, H2, H4, Fs, F0, F1, F2, B1, B2) | |
2 % [H1H2, H2H4] = func_GetH1H2_H2H4(H1, H2, H4, Fs, F0, F1, F2, B1, B2) | |
3 % Input: H1, H2, H4, vectors | |
4 % Fs - sampling frequency | |
5 % F0 - vector of fundamental frequencies | |
6 % Fx, Bx - vectors of formant frequencies and bandwidths | |
7 % Output: H1A1, H1A2, H1A3 vectors | |
8 % Notes: Function produces the corrected versions of the parameters. They | |
9 % are stored as HxHx for compatibility reasons. Use func_buildMData.m to | |
10 % recreate the mat data with the proper variable names. | |
11 % Also note that the bandwidths from the formant trackers are not currently | |
12 % used due to the variability of those measurements. | |
13 % | |
14 % Author: Yen-Liang Shue, Speech Processing and Auditory Perception Laboratory, UCLA | |
15 % Copyright UCLA SPAPL 2009 | |
16 | |
17 | |
18 if (nargin == 7) | |
19 B1 = func_getBWfromFMT(F1, F0, 'hm'); | |
20 B2 = func_getBWfromFMT(F2, F0, 'hm'); | |
21 end | |
22 | |
23 | |
24 H1_corr = H1 - func_correct_iseli_z(F0, F1, B1, Fs); | |
25 H1_corr = H1_corr - func_correct_iseli_z(F0, F2, B2, Fs); | |
26 H2_corr = H2 - func_correct_iseli_z(2*F0, F1, B1, Fs); | |
27 H2_corr = H2_corr - func_correct_iseli_z(2*F0, F2, B2, Fs); | |
28 H4_corr = H4 - func_correct_iseli_z(4*F0, F1, B1, Fs); | |
29 H4_corr = H4_corr - func_correct_iseli_z(4*F0, F2, B2, Fs); | |
30 | |
31 H1H2 = H1_corr - H2_corr; | |
32 H2H4 = H2_corr - H4_corr; | |
33 | |
34 | |
35 |