diff --git a/track_audio.m b/track_audio.m
index d79be79e9cd6326e7bd01ed610ab290fef28ca9c..ac0885996e89329778ad12e56bc4d2e03a099220 100644
--- a/track_audio.m
+++ b/track_audio.m
@@ -5,15 +5,29 @@ clc;
 % To be modified
 
 
-%% Simulation parameters
+%% Request interaural time differences (ITDs)
+requests = {'itd'};
+
+% Parameters of the auditory filterbank processor
+fb_type       = 'gammatone';
+fb_lowFreqHz  = 80;
+fb_highFreqHz = 8000;
+fb_nChannels  = 32;
+
+% Parameters of innerhaircell processor
+ihc_method    = 'dau';
+
+% Parameters of crosscorrelation processor
+cc_wSizeSec  = 0.02;
+cc_hSizeSec  = 0.01;
+cc_wname     = 'hann';
+
+% Summary of parameters
+par = genParStruct('fb_type',fb_type,'fb_lowFreqHz',fb_lowFreqHz,...
+    'fb_highFreqHz',fb_highFreqHz,'fb_nChannels',fb_nChannels,...
+    'ihc_method',ihc_method,'cc_wSizeSec',cc_wSizeSec,...
+    'cc_hSizeSec',cc_hSizeSec,'cc_wname',cc_wname);
 
-% Parameters used by the auditory front-end
-simParams.fLowHz = 80;          % Lower center frequency of the gammatone
-% filterbank in Hz
-simParams.fHighHz = 8000;       % Upper center frequency of the gammatone
-% filterbank in Hz
-simParams.nChannels = 32;       % Number of filterbank channels
-simParams.frameSize = 50E-3;    % Frame size in seconds
 
 
 %% Model parameters
@@ -39,6 +53,7 @@ addpath('./tools');
 addpath('./ekfukf-toolbox');
 
 
+
 figure(1)
 
 signal = ... % get signal here
@@ -65,11 +80,17 @@ posteriorCovariance = zeros(size(A, 1), size(A, 1), N);
 
 % Perform localization and tracking
 for l = 1:N
+    audio = get_audio();
+    dObj = dataObject(audio,fsHz);
+    % Create a manager
+    mObj = manager(dObj,requests,par);
+    % Request processing
+    mObj.processSignal();
     
     % ===================================================
     % TODO: Perform steps to get measurements inside this loop!
     % ===================================================
-%     y = get_measurement();
+    %     y = get_measurement();
     y = measuredLocations(l); % TODO: Modify this to get a measurement!
     % Perform Kalman filter prediction and update
     [x, P] = kf_predict(x, P, A, Q);