2008
DOI: 10.1121/1.2934070
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Modeling auditory attention focusing in multisource environments

Abstract: In this paper, a mathematical submodel for auditory attention focusing is discussed in the framework of our ongoing research towards a unified model for soundscape perception. The submodel implements a balance between top-down focusing, in which higher level cognition guides attention towards expected sources, and bottom-up focusing, in which attention is triggered by the noticing of sound events. Attention elasticity - the ability to switch attention between different environmental sounds - depends on the cur… Show more

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Cited by 5 publications
(4 citation statements)
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“…To minimize impact on the participants' life, we designed our interviews to last no longer than a successful marketing or fundraising interaction, i.e., 15-min (Market Research Society, 2014). Advantageously, 15-min should also be sufficient to establish a perceptual acoustic judgement, according to recent models of acoustic perception (De Coensel and Botteldooren, 2008) and to some experimental studies on planes (Breugelmans et al et al, 2017) and other traffic sources (Memoli et al, 2008; Memoli and Licitra, 2012).…”
Section: Field Interviewsmentioning
confidence: 99%
“…To minimize impact on the participants' life, we designed our interviews to last no longer than a successful marketing or fundraising interaction, i.e., 15-min (Market Research Society, 2014). Advantageously, 15-min should also be sufficient to establish a perceptual acoustic judgement, according to recent models of acoustic perception (De Coensel and Botteldooren, 2008) and to some experimental studies on planes (Breugelmans et al et al, 2017) and other traffic sources (Memoli et al, 2008; Memoli and Licitra, 2012).…”
Section: Field Interviewsmentioning
confidence: 99%
“…2.2). Other approaches rely on simulating the auditory stimuli response on individuals by moving the role covered by sound source presence into event saliency recognition [33,34,35,36,37,38], and by maintaining the cognitive and emotional factors on a higher level [32]. However, sound sources and event saliency recognition can still be considered as good indicators to fit the model.…”
Section: Introductionmentioning
confidence: 99%
“…Using the data obtained from a large-scale survey, a model based on artificial neural networks has been developed to predict soundscape perception (Yu and Kang 2009). More fundamentally, a bottom-up approach is also needed, considering the individual sensory, cognitive and emotional mechanisms (De Coensel and Botteldooren 2008;Niessen et al 2009). Modelling physics side, namely sound propagation is a space is also relevant here, where a number of models have been developed (Kang 2005;Attenborough et al 2006).…”
Section: Modellingmentioning
confidence: 99%