Abstract
In recent years, a great deal of research within the field of sound localization has been aimed at finding the acoustic cues that human listeners use to localize sounds and understanding the mechanisms by which they process these cues. In this paper, we propose a complementary approach by constructing an ideal-observer model, 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. Without regard as to how the human auditory system actually processes information, we examine the best possible localization performance that could be achieved based only on analysis of the input information, given the constraints of the normal auditory system. We show that the model performance is generally in good agreement with the actual human localization performance, as assessed in a meta-analysis of many localization experiments (Best et al. in Principles and applications of spatial hearing, pp 14–23. World Scientific Publishing, Singapore, 2011). We believe this approach can shed new light on the optimality (or otherwise) of human sound localization, especially with regard to the level of uncertainty in the input information. Moreover, the proposed model allows one to study the relative importance of various (combinations of) acoustic cues for spatial localization and enables a prediction of which cues are most informative and therefore likely to be used by humans in various circumstances.
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Acknowledgments
We would like to thank Virginia Best for providing us with Fig. 1 and the data, used in the meta-analysis reported on in Best et al. (2011). We would also like to thank the reviewers for their thorough reading of the manuscript. Their comments and suggestions clearly improved the manuscript. We acknowledge the support of the Australian Research Council Discovery Project funding scheme (ARC DP110102920).
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Reijniers, J., Vanderelst, D., Jin, C. et al. An ideal-observer model of human sound localization. Biol Cybern 108, 169–181 (2014). https://doi.org/10.1007/s00422-014-0588-4
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DOI: https://doi.org/10.1007/s00422-014-0588-4