function [outp] = dietz2011_interauralfunctions(insig,fs,fc,varargin)
%dietz2011_interauralfunctions Interaural stages of Dietz 2011
%
% Input parameters
% insig : input signal
% fs : sampling frequencies
% fc : center frequencies
%
% Output parameters:
% outp : Structure containing the output. See the description
% below.
%
% Calculate interaural parameters like interaural transfer function (ITF),
% interaural phase difference (IPD), interaural time difference (ITD) and
% interaural coherence (IC) for the given input signals. The ITD is calculated
% by dividing the IPD by the instantaneous frequency of the signal. In
% addition lowpassed filtered version of the interaural parameters are
% calculated (ending with _lp) to simulate a finite time resolution of the
% binaural system.
%
% The output structure outp contains the following fields:
% itf : transfer function
% ipd : phase difference in rad
% itd : interaural time difference based on instantaneous frequency
% itd_C : interaural time difference based on center frequency
% f_inst_1 : instantaneous frequencies of left ear signal
% f_inst_2 : instantaneous frequencies of right ear canal signal
% f_inst : instantaneous frequencies (average of f_inst1 and 2)
% ic : interaural coherence
% rms : rms value of frequency channels for weighting
% ild_lp : based on low passed-filtered insig, level difference in dB
% ipd_lp : based on lowpass-filtered itf, phase difference in rad
% itd_lp : based on lowpass-filtered itf, interaural time difference
% itd_C_lp : based on lowpass-filtered itf, interaural time difference
%
% The _lp values are not returned if the 'nolowpass' flag is set.
%
% DIETZ2011_INTERAURALFUNCTIONS accepts the following optional parameters:
%
% 'compression_power',cpwr
% Applied compression of the signal on the cochlea with
% ^compression_power. The default value is 0.4.
%
% 'tau_cycles',tau_cycles
% Temporal resolution of binaural processor in terms of
% cycles per frequency channel. The default value is 5.
%
% 'signal_level_dB_SPL',signal_level
% Sound pressure level of left channel. Used for data
% display and analysis. Default value is 70.
%
% 'lowpass' Calculate the interaural parameters of the lowpassed
% signal/ITF (_lp return values). This is the default.
%
% 'nolowpass' Don't calculate the lowpass based interaural parameters.
% The _lp values are not returned.
%
% See also: dietz2011, dietz2011_filterbank
%
% References:
% M. Dietz, S. D. Ewert, and V. Hohmann. Auditory model based direction
% estimation of concurrent speakers from binaural signals. Speech
% Communication, 53(5):592-605, 2011. [1]http ]
%
% References
%
% 1. http://www.sciencedirect.com/science/article/pii/S016763931000097X
%
%
% Url: http://amtoolbox.sourceforge.net/amt-0.9.9/doc/modelstages/dietz2011_interauralfunctions.php
% Copyright (C) 2009-2015 Piotr Majdak and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 0.9.9
%
% 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: Mathias Dietz, Martin Klein-Hennig (for AMT), Hagen Wierstorf (for AMT)
if nargin<3
error('%s: Too few input parameters.',upper(mfilename));
end;
if ~isnumeric(insig)
error('%s: insig has to be a numeric signal!',upper(mfilename));
end
if ~isnumeric(fs) || ~isscalar(fs) || fs<=0
error('%s: fs has to be a positive scalar!',upper(mfilename));
end
if ~isnumeric(fc)
error('%s: fc has to be a numeric signal!',upper(mfilename));
end
definput.import = {'dietz2011_interauralfunctions'};
[flags,kv] = ltfatarghelper({},definput,varargin);
% if signal contains no frequency channels return empty
if size(insig,2)==0, outp = []; return; end
% ----- interaural parameters -----
% interaural transfer function (ITF), eq. 2 in Dietz (2011)
outp.itf = insig(:,:,2) .* conj(insig(:,:,1));
% interaural phase difference (IPD), eq. 3 in Dietz (2011) but without low pass
% filtering
outp.ipd = angle(outp.itf);
% instantaneous frequency (f_inst), eq. 4 in Dietz (2011)
for k = 1:length(fc)
outp.f_inst_left(:,k) = calc_f_inst(insig(:,k,1),fs);
outp.f_inst_right(:,k) = calc_f_inst(insig(:,k,2),fs);
end
outp.f_inst = max(eps,0.5*(outp.f_inst_left + outp.f_inst_right)); % to avoid division by zero
% interaural time difference (ITD), based on instantaneous frequencies
outp.itd = 1/(2*pi)*outp.ipd./outp.f_inst;
% interaural time difference (ITD), based on center frequencies <== is this really needed?
for k = 1:length(fc)
outp.itd_C(:,k) = 1/(2*pi)*outp.ipd(:,k)/fc(k);
end
% ----- low pass versions of interaural parameters -----
% The low pass is simulating a finite time resolution of the binaural system and
% is given by the coh_cycles parameter
tau = kv.tau_cycles./fc;
if flags.do_lowpass
a = exp( -1./(fs.*tau) );
% interaural phase difference (IPD) of lowpassed signals, eq. 3 in Dietz (2011)
outp.ipd_lp = angle(lowpass(outp.itf,a));
outp.f_inst_lp = lowpass(outp.f_inst,a);
outp.itd_lp = 1/(2*pi)*outp.ipd_lp./outp.f_inst_lp;
for k = 1:length(fc)
outp.itd_C_lp(:,k) = 1/(2*pi)*outp.ipd_lp(:,k)/fc(k);
end
% interaural level difference
inoutsig = lowpass(abs(insig),a);
inoutsig(abs(inoutsig)<eps) = eps; % avoid division by zero and log(0)
outp.ild_lp = 20./kv.compression_power.*log10(inoutsig(:,:,2)./inoutsig(:,:,1));
end
% interaural coherence (IC) estimated by interaural vector strength (IVS), see
% eq. 7 in Dietz (2011)
outp.ic = interaural_vector_strength(outp.itf, tau, fs);
% weighting of channels for cumulative ixd determination
% sqrt(2) is due to half-wave rectification (included 28th Sep 07)
outp.rms = kv.signal_level_dB_SPL*kv.compression_power + 20*log10(sqrt(2)*min(rms(squeeze(abs(insig(:,:,1)))),rms(squeeze(abs(insig(:,:,2))))));
outp.rms = max(outp.rms,eps); % avoid negative weights
end
%% ----- internal functions -----
% lowpass
function outsig = lowpass(sig, a)
% outsig = lowpass(sig, a)
% This is a simple low-pass filter y(n) = (1-a)*x(n) - a*y(n-1)
% Meaning of parameter a:
% a - damping coefficient (0 - no filtering, 1 - flat output)
% tau = 1/(2*pi*f_c) where f_c is the cutoff frequency of the filter
% a = exp(-1/(fs*tau)) where fs - sampling frequency
%
if ndims(sig)==3
sig = permute(sig,[1 3 2]); % => [samples ears channels]
channels = size(sig,3);
outsig = zeros(size(sig));
for ii=1:channels
outsig(:,:,ii) = filter([1-a(ii)], [1, -a(ii)], sig(:,:,ii));
end
outsig = permute(outsig,[1 3 2]); % => [samples channels ears]
else
channels = size(sig,2);
outsig = zeros(size(sig));
for ii=1:channels
outsig(:,ii) = filter([1-a(ii)], [1, -a(ii)], sig(:,ii));
end
end
end
% Hagen: I have removed the temporal smoothing from this function. The lowpass
% has to be applied afterwards. The positive effect is a little bit smoother ITD
% value. The negative effect is a longer time after the onset at the beginning
% to reach the actual value.
function f_inst = calc_f_inst(sig,fs)
% function f_inst = calc_f_inst(sig,fs);
%
% Calculates instantaneous frequency from a complex (analytical) signal
% using first order differences
%
% input parameters:
% sig : complex (analytical) input signal
% fs : sampling frequency of sig
%
% output values:
% f_inst: vector of estimated inst. frequency values
%
% copyright: Universitaet Oldenburg
% author : volker hohmann
% date : 12/2004
sig = sig./(abs(sig)+eps);
f_inst = [0; sig(2:end).*conj(sig(1:end-1))];
f_inst = angle(f_inst)/2/pi*fs;
end
% Calculate the interaural coherence (IC) with the help of the interaural vector
% strength (IVS) as defined by eq. 7 in Dietz (2011)
function ivs = interaural_vector_strength(itf,tau_coherence,fs)
%tau_coherence = 15e-3; % good value for ipd_fine
c_coh = exp(-1./(fs.*tau_coherence));
if length(tau_coherence)==1
ivs = abs(filter(1-c_coh,[1 -c_coh],itf))./abs(filter(1-c_coh,[1 -c_coh],abs(itf)));
elseif length(tau_coherence)==size(itf,2)
ivs = zeros(size(itf));
for n=1:length(tau_coherence)
ivs(:,n) = abs(filter(1-c_coh(n),[1 -c_coh(n)],itf(:,n)))./ ...
abs(filter(1-c_coh(n),[1 -c_coh(n)],abs(itf(:,n))));
end
else
error('wrong number of tau_coherence values')
end
end
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