Usage

[E,cues,cueLabels] = baumgartner2020( target,template )

Input parameters

target : binaural impulse response(s) referring to the directional

transfer function(s) (DFTs) of the target sound(s).

Option 1: given in SOFA format -> sagittal plane DTFs will be extracted internally.

Option 2: binaural impulse responses of all available listener-specific DTFs of the sagittal plane formated according to the following matrix dimensions: time x direction x channel/ear

template : binaural impulse responses of all available

listener-specific DTFs of the sagittal plane referring to the perceived lateral angle of the target sound. Options 1 & 2 equivalent to target.

Output parameters

E : predicted degree of externalization

cues : outcomes of individual cues

cueLabels : cue labels; cell array with 1st col. denoting acronyms

and 2nd column for descriptions

baumgartner2019(...) is a model for sound externalization. It bases on the comparison of the intra-aural internal representation of the incoming sound with a template and results in a probabilistic prediction of polar angle response.

baumgartner2020 accepts the following optional parameters:

'cueWeights',cW : Set the weights of individual cues to determine the

final externalization score. Cue-specific weights (entered as a vector) are ordered as follows:

1. monaural spectral similarity (MSS)
2. interaural spectral similarity of ILDs (ISS)
3. spectral standard deviation of monaural gradients (MSSD)
4. spectral standard deviation of ILDs (ISSD)
5. interaural broadband time-intensity coherence (ITIT)
6. interaural coherence (IC)
7. monaural intensity difference (MI)
8. temporal standard deviation of ILDs (ITSD).

Default weights are 0.67 for MSS, 0.33 for ITIT, and 0 for all others.

'S',S : Set the cue-specific sensitivity parameter to S.

1/S represents the slope of sigmoidal mapping function. Vector order equivalent to cueWeights. Default values are determined by the weighted average sensitivities determined in Baumgartner and Majdak (2020) - run exp_baumgartner2020('tab2') to show them.

'lat',lat : Set the apparent lateral angle of the target sound to lat.

Default value is 0 degree (median SP).

'range',c1 : Set the range factor of the externalization scores to c1.

Default value is 3.78 from Hassager et al. (2016).

'offset',c2 : Set the offset of the externalization score to c2.

Default value is 1 from Hassager et al. (2016).

'ILD_JND',L : Set the just noticeable ILD difference to L from the

internal template. Default value is 1 (dB).

ITD_JND',T : Set the just noticeable ITD difference to T from the

internal template. Default value is 20e-6 (s).

baumgartner2020 accepts the following flags:

'LTA' : Looser-takes-all strategy: Model selects minimal

predicted externalization scores across cues with weights larger than zero.

Requirements:

1. SOFA API from http://sourceforge.net/projects/sofacoustics for Matlab (in e.g. thirdparty/SOFA)
2. Data in hrtf/baumgartner2017
3. Circular Statistics Toolbox from http://www.mathworks.com/matlabcentral/fileexchange/10676-circular-statistics-toolbox--directional-statistics-