Issue |
Acta Acust.
Volume 7, 2023
Topical Issue - Auditory models: from binaural processing to multimodal cognition
|
|
---|---|---|
Article Number | 12 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/aacus/2023006 | |
Published online | 01 May 2023 |
Scientific Article
A Bayesian model for human directional localization of broadband static sound sources
1
Acoustics Research Institute, Austrian Academy of Sciences, 1040 Vienna, Austria
2
Department of Management and Engineering, University of Padova, 36100 Vicenza, Italy
3
Dyson School of Design Engineering, Imperial College London, London, United Kingdom
4
Department of Computer Science, University of Milano, 20133 Milan, Italy
* Corresponding author: roberto.barumerli@oeaw.ac.at
Received:
5
June
2021
Accepted:
13
March
2023
Humans estimate sound-source directions by combining prior beliefs with sensory evidence. Prior beliefs represent statistical knowledge about the environment, and the sensory evidence consists of auditory features such as interaural disparities and monaural spectral shapes. Models of directional sound localization often impose constraints on the contribution of these features to either the horizontal or vertical dimension. Instead, we propose a Bayesian model that flexibly incorporates each feature according to its spatial precision and integrates prior beliefs in the inference process. The model estimates the direction of a single, broadband, stationary sound source presented to a static human listener in an anechoic environment. We simplified interaural features to be broadband and compared two model variants, each considering a different type of monaural spectral features: magnitude profiles and gradient profiles. Both model variants were fitted to the baseline performance of five listeners and evaluated on the effects of localizing with non-individual head-related transfer functions (HRTFs) and sounds with rippled spectrum. We found that the variant equipped with spectral gradient profiles outperformed other localization models. The proposed model appears particularly useful for the evaluation of HRTFs and may serve as a basis for future extensions towards modeling dynamic listening conditions.
Key words: Sound localization / Auditory model / Bayesian inference / HRTF / Behavior
© The Author(s), Published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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