function output = joergensen2011_combineinformation(input,SNRs,conditions,Nsp)
%joergensen2011_combineinformation Combine information
% Usage: output = joergensen2011_combineinformation(input,SNRs,conditions,Nsp);
%
% Input parameters:
% input : Cell array with the SNRenv results for each
% processing condition (n),SNR (k), and speech sample (q)
% SNRs : Vector with the SNRs used
% conditions : Vector with the procssing conditions used.
% Nsp : Number the number of speech samples in the XXX
%
% Output parameters:
% output : Structure containing the following fields:
%
% output.combined_aud
% [n,k] Matrix with overall SNRenv
% for each processing condition and SNR
%
% output.SNRenvs
% Cell array {n,k,q} with entries for each
% condition, SNR, and speech sample. Each entry
% is Matrix with an SNRenv value for each XXX
%
% JOERGENSEN2011_COMBINEINFORMATION(input,SNRs,conditions,Nsp) combines
% the SNRenv across modulation and audio filters. It is also possible to
% extracts other information such as the excitation patterns or long-term
% spectra.
%
% XXX Better description
%
%
% Url: http://amtoolbox.sourceforge.net/amt-0.10.0/doc/modelstages/joergensen2011_combineinformation.php
% Copyright (C) 2009-2020 Piotr Majdak and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 1.0.0
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
% Author: Søren Jørgensen august 2010
if nargin <6
TimeSpectra = 'no';
end
if nargin <5
ExPatterns = 'no';
end
res = input;
for q = 1:Nsp %for each of the speech samples
for n = conditions %for each of the processing conditions
for k = 1:length(SNRs) %for each SNR
Output_tmp = res{n,k,q};
% extracting the SNRenvs from the internal representation:
%
SNRenvs{n,k,q} = Output_tmp.outSNRenvs(:,:);
% ------------------ Combining information --------------------------------
tmp = SNRenvs{n,k,q};
% Converting to linear values:
linear = 10.^(tmp*.1);
linear(find(tmp == 0)) = 0;
combined_mod_tmp = sqrt(sum(linear.^2,1)); % Combining across modulation filters using integration model (Green and Swets 1988)
combined_aud(n,k,q) = (sqrt(sum(combined_mod_tmp.^2)));% Combining across auditory filters
clear combined_mod_tmp;
end
end
end
%
% saving output:
output.combined_aud = combined_aud;
output.SNRenvs = SNRenvs;