BARUMERLI2022 - Bayesian spherical sound localization model (multi-feature)

Usage

[m] = barumerli2022(sofa_obj);
[m] = barumerli2022(template,target);

Input parameters

sofa_obj

valid SOFA object containing listener HRTFs. The model computes the templates and the targets from the direction in the object. Then, the model estimates all the directions in the SOFA object.

Output parameters

`m`	(matrix) table organized as in localizationerror.m with actual and predicted directions. Consider barumerli2022_metrics for the analysis of such matrix.
`doa`	(stuct) data struct containg the field .estimations and .posterior. The first is a matrix with dimensions [target_num, kv.num_exp, 3] and coordinates are stored in cartesian coordinates. The second provide the computed posterior distribution for further elaborations and its dimensions are [target_num, template_num, kv.num_exp).
`coords`	(object) actual directions of the binaural sounds in target struct.

Description

barumerli2022(...) is an ideal-observer model of human sound localization, by which we mean a model that performs optimal information processing within a Bayesian context. The model considers all available spatial information contained within the acoustic signals encoded by each ear. Parameters for the optimal Bayesian model are determined based on psychoacoustic discrimination experiments on interaural time difference and sound intensity.

Additional input parameters:

`'num_exp'`	Number of repetitions. For each target repeat the experiment num_exp times. Default: 1
`'sigma_itd'`	Standard deviation associated to noise added to the ITD feature. Default: 0.569
`'sigma_ild'`	Standard deviation associated to noise added to the ILD feature. Default: 1
`'sigma_spectral'`	Standard deviation associated to noise added to the spectral features. Default: 1
`'sigma_prior'`	Standard deviation of the prior distribution. If set to empty [], a uniform distribution is considered. Default:11.5
`'sigma_motor'`	Standard deviation of the motor noise. Default: 10

If no SOFA object is provided then the model requires:

`'template'`	internal representation specified by a specific feature space. Refer to barumerli2022_featureextraction for its computation.
`'target'`	preprocessed target struct with the binaural sounds of which the direction has to be estimated. Refer to barumerli2022_featureextraction for its computation.