Usage

[Obj,results]=ziegelwanger2014(data,estimation,outlierDetection,model,p0_onaxis)

Input parameters

estimation (optional)

select one of the estimation methods

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1: Threshold-Detection 2: Centroid of squared IR 3: Mean Groupdelay 4: Minimal-Phase Cross-Correlation (Max) (default) [TOAest]: pre-estimated TOAs

outlierDetection (optional)

detect outliers in estimated TOAs

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0: off 1: on (default values: [0.05;0.01]) [alpha r]: rejects outliers using the extreme Studentized

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deviance test with the significance level of ALPHA and upper bound of outlier rate R.

model (optional)

correct estimated toa, using geometrical TOA-Model

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0: TOA estimated 1: off-axis TOA modeled (default) 2: on-axis TOA modeled

p0_onaxis (optional)

startvalues for lsqcurvefit

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dim 1: [sphere-radius in m,

azimut of ear in radiants, elevation of ear in radiants, direction-independent delay in seconds]

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dim 2: each record channel

Output parameters

results.toa

data matrix with time of arrival (TOA) for each impulse response (IR):

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dim 1: each toa in samples dim 2: each record channel

results.p_onaxis

estimated on-axis model-parameters

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dim 1: [sphere-radius in m,

azimut of ear in radiants, elevation of ear in radiants, direction-independent delay in seconds]

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dim 2: each record channel

results.p_offaxis

estimated off-axis model-parameters

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dim 1: [sphere-radius in m,

xM in m, yM in m, zM in m, direction-independent delay in seconds, azimut of ear in radiants, elevation of ear in radiants]

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dim 2: each record channel

Description

Estimates the Time-of-Arrival for each measurement in Obj (SOFA) and corrects the results with a geometrical model of the head.

Requirements:

1. SOFA API from http://sourceforge.net/projects/sofacoustics for Matlab (in e.g. thirdparty/SOFA)
2. Optimization Toolbox for Matlab
3. Data in hrtf/ziegelwanger2014

Examples:

To calculate the model parameters for the on-axis time-of-arrival model (p_onaxis) and for the off-axis time-of-arrival model (p_offaxis) for a given HRTF set (SOFA object, 'Obj') with the minimum-phase cross-correlation estimation, use:

[Obj,results]=ziegelwanger2014(Obj,4,1);