Modeling spatial auditory attention in ACT-R: a constraint-based approach

Attention is the focus of a considerable amount of research in cognitive modeling. Yet, most of the work has been devoted to studying visual attention. Auditory attention differentiates itself from visual attention in many ways. For example, it is often important for our survival to attend to auditory events at a distance and out of sight. Due to limitations on attentional resources, audition must strike a balance between monitoring the environment and attending to current tasks. In this paper, we provide an overview of our previous work which models auditory attention as a spatial gradient made up of a combination of top-down and bottom-up influences [14, 15]. We also present how the model is currently integrated with the audio module in ACT-R. Our approach uses the well-established AI framework of constraint satisfaction problems to model how auditory attention is allocated over space and it is organized around three main components: a goal map, a saliency map, and a priority map. The goal map models the distribution of attention which is allocated by choice (top-down component). The saliency map, as the name suggests, models attention related to the saliency of auditory stimuli (bottom-up component) and the priority map synthesizes the other two maps in an overall distribution of the attentional bias. This model was shown to be successful in reproducing behavioral data of experiments where there is a single attended location. Its integration into a cognitive architecture opens up new possibilities for evaluation in the context of other cognitive functions and in modeling tasks and designing systems where audition is important. (C) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 9th Annual International Conference on Biologically Inspired Cognitive Architectures.