function periphOutput = takanen2013periphery(insig,fs,outputPlot)
%TAKANEN2013PERIPHERY Process the input through the model of periphery
% Usage: periphOutput = takanen2013periphery(insig,fs,outputPlot);
% periphOutput = takanen2013periphery(insig,fs);
%
% Input parameters:
% insig : binaural input signal to be processed. Optionally,
% the output of the cochlear model by Verhulst et. al.
% 2012 can be used as well
% fs : sampling rate
% outputPlot : boolean value that defines whether the periphery
% model output at different frequency bands are plotted
%
% Output parameters:
% periphOutput : Structure consisting of the following elements
%
% periphOutput.left
% Left ear "where" stream output
%
% periphOutput.right
% Right ear "where" stream output
%
% periphOutput.fc
% Characteristic frequencies
%
% periphOutput.ventralLeft
% Left hemisphere "what" stream output
%
% periphOutput.ventralLeft
% Right hemisphere "what" stream output
%
% This function processes the binaural input signal through the model of
% periphery presented by Takanen, Santala, Pulkki 2013, the model which
% consists of a nonlinear time-domain model of cochlea and model of
% cochlear nucleus. The processing contains the following steps:
%
% 1) the binaural input signal is processed with the nonlinear time-
% domain model of cochlea by Verhulst et. al. 2013 to obtain the
% velocity of basilar membrane movement at different positions
%
% 2) the obtained velocity information is half-wave rectified
%
% 3) the half-waves are replaced with Gaussian pulses centered around
% the local maxima of the half-waves
%
% 4) the frequency-dependent delays of the cochlea model are
% compensated
%
% See also: takanen2013, verhulst2012
%
% Url: http://amtoolbox.sourceforge.net/amt-0.9.7/doc/modelstages/takanen2013periphery.php
% Copyright (C) 2009-2014 Peter L. Søndergaard and Piotr Majdak.
% This file is part of AMToolbox version 0.9.7
%
% 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/>.
% References: takanen2014 pulkki2009 verhulst2012
%
% AUTHOR: Marko Takanen, Olli Santala, Ville Pulkki
%
% COPYRIGHT (C) 2013 Aalto University
% School of Electrical Engineering
% Department of Signal Processing and Acoustics
% Espoo, Finland
%% ------ Check the input arguments ---------------------------------------
if nargin<3
outputPlot =0;
end
%specify the characteristic frequencies of the model
fc = erbtofreq(4:39);
spl = 60; % sound pressure level of the input signal
%% ------ Process the binaural input with the cochlear model --------------
if isstruct(insig)
% input to the periphery model can be also a output of the Verhulst
% cochlear model
cochlear = insig;
else
norm_factor=max(abs(insig(:,1))); %first channel as reference for rms normalization
insig(:,1)=insig(:,1)./norm_factor;
insig(:,2)=insig(:,2)./norm_factor;
[V,Y,E,CF] = verhulst2012(insig,fs,fc,[spl spl]);
cochlear.velocityLeft=V(:,:,1);
cochlear.velocityRight=V(:,:,2);
end
%load a vector of frequency specific delays computed for the Verhulst model
%outputs at fc
x=amtload('takanen2013','cochleardelays.mat');
cochlear.delaysV = x.velocitydelays;
%use the velocity of the basilar membrane movement as input to CN model
processed.left = cochlear.velocityLeft;processed.right = cochlear.velocityRight;
[nVals nBands] = size(processed.left);
%% ------ Half-wave rectification -----------------------------------------
processed.left= processed.left.*(processed.left >0);
processed.right= processed.right.*(processed.right >0);
periphOutput.ventralLeft = processed.right;
periphOutput.ventralRight = processed.left;
%% ------ Impulse generation ----------------------------------------------
%search of the local maximas of each half-wave separately for left and
%right ear signals
for chanInd=1:nBands
left = processed.left(:,chanInd);
right = processed.right(:,chanInd);
processed.left(:,chanInd) = zeros(nVals,1);
processed.right(:,chanInd) = zeros(nVals,1);
%start end end points for each half-wave
startingPoints = strfind((left'>0),[0 1]);
endpoints = [strfind((left'>0),[1 0])+1 length(left)];
if (isempty(startingPoints) && ~isempty(endpoints))
startingPoints = 1;
else
if startingPoints(1)>=endpoints(1)
startingPoints = [1 startingPoints];
end
end
rmsVals=zeros(size(startingPoints));
locations = rmsVals;
nsamples = endpoints(1:length(startingPoints))-startingPoints+1;
%compute the rms values of each half-wave and position it at the local
%maximum
for locInd=1:length(startingPoints)
rmsVals(locInd)= norm(left(startingPoints(locInd):endpoints(locInd)))/sqrt(nsamples(locInd));
[unnecessary, locations(locInd)] = max(left(startingPoints(locInd):endpoints(locInd)));
end
processed.left(locations+startingPoints-1,chanInd) = rmsVals';
%processing of the right channel
%start end end points for each half-wave
startingPoints = strfind((right'>0),[0 1]);
endpoints = [strfind((right'>0),[1 0])+1 length(right)];
if (isempty(startingPoints) && ~isempty(endpoints))
startingPoints = 1;
else
if startingPoints(1)>=endpoints(1)
startingPoints = [1 startingPoints];
end
end
%compute the rms values of each half-wave and position it at the local
%maximum
rmsVals= zeros(size(startingPoints));locations = rmsVals;
nsamples = endpoints(1:length(startingPoints))-startingPoints+1;
for locInd=1:length(startingPoints)
rmsVals(locInd)= norm(right(startingPoints(locInd):endpoints(locInd)))/sqrt(nsamples(locInd));
[unnecessary, locations(locInd)] = max(right(startingPoints(locInd):endpoints(locInd)));
end
processed.right(locations+startingPoints-1,chanInd) = rmsVals';
end
%% ------ Convolution with Gaussian window-functions ----------------------
% the width of the Gaussian window in the peripheral hearing model depends
% on the center frequency
N = zeros(size(fc));
N(fc<800) = round((2./fc(fc<800))*fs);
indMid = find(((800<=fc).*(fc<=2800))==1);N(indMid) = round(0.0024*(0.6+0.4*fc(indMid)./800)*fs);
N(fc>2800) = round(0.0048*fs);
% the constant alpha is set to 20
alpha=20;
periphOutput.left = zeros(nVals,nBands);periphOutput.right = periphOutput.left;
for chanInd=1:nBands
left = processed.left(:,chanInd);
right = processed.right(:,chanInd);
n = -N(chanInd)/2:1:N(chanInd)/2;
winFunction = (exp(-0.5*(alpha*n/(N(chanInd)/2)).^2))';
%convolution with the gaussian window function
left = (1/sum(winFunction))*conv(left,winFunction,'same');
right = (1/sum(winFunction))*conv(right,winFunction,'same');
%% compensation for the cochlear model delays
periphOutput.left(:,chanInd) = [left(cochlear.delaysV(chanInd)+1:end);zeros(cochlear.delaysV(chanInd),1)];
periphOutput.right(:,chanInd) = [right(cochlear.delaysV(chanInd)+1:end);zeros(cochlear.delaysV(chanInd),1)];
periphOutput.ventralLeft(:,chanInd) = [periphOutput.ventralLeft(cochlear.delaysV(chanInd)+1:end,chanInd);zeros(cochlear.delaysV(chanInd),1)];
periphOutput.ventralRight(:,chanInd) = [periphOutput.ventralRight(cochlear.delaysV(chanInd)+1:end,chanInd);zeros(cochlear.delaysV(chanInd),1)];
end
periphOutput.fc = fc;
%% ------ Plot the periphery model output, if desired ---------------------
if outputPlot
figure(90);
g(1) = subplot(6,1,1);plot((0:length(insig(:,1))-1)./(fs/1000),insig(:,1));ylabel('Input');set(gca,'yTick',[]);
g(2) = subplot(6,1,2);plot((0:size(periphOutput.left,1)-1)./(fs/1000),periphOutput.left(:,4));title([num2str(round(fc(4))) ' Hz']);
g(3) = subplot(6,1,3);plot((0:size(periphOutput.left,1)-1)./(fs/1000),periphOutput.left(:,9));title([num2str(round(fc(9))) ' Hz']);
g(4) = subplot(6,1,4);plot((0:size(periphOutput.left,1)-1)./(fs/1000),periphOutput.left(:,16));title([num2str(round(fc(16))) ' Hz']);
g(5) = subplot(6,1,5);plot((0:size(periphOutput.left,1)-1)./(fs/1000),periphOutput.left(:,22));title([num2str(round(fc(22))) ' Hz']);
g(6) = subplot(6,1,6);plot((0:size(periphOutput.left,1)-1)./(fs/1000),periphOutput.left(:,28));title([num2str(round(fc(28))) ' Hz']);
xlabel('Time [ms]');
linkaxes(g,'x');
clear g
end