THE AUDITORY MODELING TOOLBOX

Applies to version: 1.5.0

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DATA_PAUSCH2022 - Results from Pausch et al. (2022)

Usage:

[data,itd] = data_pausch2022()
[data,itd] = data_pausch2022(flags)
weights = data_pausch2022('weights', flags)
features = data_pausch2022('features', flags)

Input parameters:

flags select the type of spatial transfer function (STF) and model, see below.

Output parameters:

data

Structure with the STFs:

  • id: the participant ID if flag is 'hrtf', 'hartf_front', or 'hartf_rear'
  • sofa: individual STFs as a SOFA structure if flag is 'hrtf', 'hartf_front', or 'hartf_rear'
itd

Estimated ITDs for directions in the horizontal plane:

  • itd_hor: ITDs (in s)
  • itd_max: maximum ITD (in s)
  • itd_arg_max_idx: index of the argument of the the maximum ITD
  • itd_arg_max_phi: argument of the the maximum ITD (in deg)
  • itd_hor_mean: direction-dependent mean ITDs across participants (in s)
  • itd_hor_std: direction-dependent standard deviation of ITDs across participants (in s)
  • bp_fc_low: lower cut-off frequency (Hz) of the bandpass filter applied before estimating the ITDs
  • bp_fc_high: upper cut-off frequency (Hz) of the bandpass filter applied before estimating the ITDs
weights Matrix of (M*P+1) x N polynomial regression weights (degree of P=4) to be applied on a subset of M=5 individual features. For the model pausch, N=4. For other models, N=1.
features Individual anthropometric features and subject IDs as in Pausch et al. (2022)

Description:

data_pausch2022(...) returns spatial transfer function (STFs) and ITDs calculated for a specified model.

data_pausch2022('weights',...) returns the polynomial regression weights.

data_pausch2022('features',...) returns the individual features.

The following STFs flags can be selected:

'hrtf' load individual HRTF datasets
'hartf_front' load invidual front HARTF datasets (default)
'hartf_rear' load invidual rear HARTF datasets

The following ITD model flags can be selected (only required if weights are selected):

'pausch2022' hybrid ITD model by Pausch et al. (2022) (default)
'kuhn1977' analytic ITD model by Kuhn (1977)
'woodworth1954' analytic ITD model by Woodworth and Schlosberg (1954)
'aaronson2014' analytic ITD model by Woodworth and Schlosberg (1954) extended by Aaronson and Hartmann (2014)

Additional key/value pairs include:

'bp_fc_low' lower cut-off frequency (Hz) of the bandpass filter applied before estimating the ITDs (default: []) [double]
'bp_fc_high' upper cut-off frequency (Hz) of the bandpass filter applied before estimating the ITDs (default: []) [double]

Further information on key/value pairs can be found in arg_pausch2022.m

Requirements:

  1. SOFA Toolbox from http://sourceforge.net/projects/sofacoustics for Matlab
  2. Data in auxdata/pausch2022 (downloaded on the fly)

References:

F. Pausch, S. Doma, and J. Fels. Hybrid multi-harmonic model for the prediction of interaural time differences in individual behind-the-ear hearing-aid-related transfer functions. Acta Acust., 6:34, 2022. [ DOI | http ]

G. F. Kuhn. Model for the interaural time differences in the azimuthal plane. The Journal of the Acoustical Society of America, 62(1):157--167, 1977. [ DOI | arXiv | http ]

R. S. Woodworth and H. Schlosberg. Experimental psychology, Rev. ed. Holt, Oxford, England, 1954.

N. L. Aaronson and W. M. Hartmann. Testing, correcting, and extending the Woodworth model for interaural time difference. The Journal of the Acoustical Society of America, 135(2):817--823, 2014. [ DOI | arXiv | http ]

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