THE AUDITORY MODELING TOOLBOX

Applies to version: 1.6.0

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barumerli2024_mockup
FrAMBI agent performing a mock-up vertical-plane sound localization

Usage:

[agent, options] = barumerli2024_mockup();
[agent, options] = barumerli2024_mockup(options);

Input parameters:

options Optional structure representing the FrAMBI options.
agent

Structure representing the FrAMBI agent. See the general description of FrAMBI for more details. In addition, the following agent-specific fields are created:

  • name: String describing the agent. Default: 'Vertical-Plane Localization Mockup'.
  • model: Structure defining the functionality of agent by storing functions handles in fields initialize, observe, infer, act, and respond.
  • state.parameters: Parameter structure as in frambi_parameters with:
    • angular_uncertainty: The angular uncertainty (i.e., the angular standard deviation in the processing, in degrees). Default: 22.7 degrees, as in Tab. I, Middlebrooks (1999).
    • confusion_rate: The rate (as ratio) of confusing front and back when localizaing the source. Default: 0.046, as in Tab. I, Middlebrooks (1999).
options Structure representing the FrAMBI options. No agent-specific fields are added.

Description:

barumerli2024_mockup(..) returns a structure describing a mock-up agent performing vertical-plane sound-source localization. The agent accounts for angular uncertainty and front-back confusions.

barumerli2024_mockup(..) also creates an empty structure with FrAMBI options or passes options if provided as input.

Note that this agent is just a mock up to demonstrate some FrAMBI functionality. This agent does not handle actual sounds, instead, it uses a mock-up environment (from sig_barumerli2024, which provides the target angle directly). Specifically, barumerli2024_mockup(..) defines defines the following functionality linked with local functions:

  • model.observe is linked with local_observe, which adds front-back confusions and sensory noise to the actual target angle.
  • model.infer is linked with local_infer, which uses directly the observation as the inference (i.e., the agent trusts the observation).
  • model.act is linked with local_act, in which the action is directly the inference (i.e., the target angle is the action).
  • model.respond is linked with local_respond, which responses with the action, which is the actual target angle.

References:

R. Barumerli and P. Majdak. FrAMBI: A Software Framework for Auditory Modeling Based on Bayesian Inference. under review at Neuroinformatics, 2024.

P. Majdak, M. J. Goupell, and B. Laback. 3-D localization of virtual sound sources: Effects of visual environment, pointing method and training. Atten Percept Psycho, 72:454--469, 2010.

J. C. Middlebrooks. Virtual localization improved by scaling nonindividualized external-ear transfer functions in frequency. The Journal of the Acoustical Society of America, 106:1493--1510, 1999.

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