Bert De Coensel

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A computational model of auditory attention to environmental sound, inspired by the structure of the human auditory system, is presented. The model simulates how listeners switch their attention over time between different auditory streams, based on bottom-up and top-down cues. The bottom-up cues are determined by the time-dependent saliency of each stream.(More)
Environmental sound measurement networks are increasingly applied for monitoring noise pollution in an urban context. Intelligent measurement nodes offer the opportunity to perform advanced analysis of environmental sound, but tradeoffs between cost and functionality still have to be made. When using a tiered architecture, local nodes with limited computing(More)
Recent studies show that introducing sound from water features in urban open spaces may reduce the loudness of road traffic noise, but it is not clear in which situations this measure also improves overall soundscape quality. This work describes a listening experiment on loudness, pleasantness, and eventfulness of stimuli that combine road traffic noise(More)
Artificial intelligence traditionally draws inspiration from biological systems, in order to achieve a similar degree of intelligence in artificial systems. More recently, ideas from computational intelligence are being applied successfully in achieving a better understanding of the mechanisms underlying the emergence of group-level patterns in biological(More)
Auditory attention is an essential property of human hearing. It is responsible for the selection of information to be sent to working memory and as such to be perceived consciously, from the abundance of auditory information that is continuously entering the ears. Thus, auditory attention heavily influences human auditory perception and systems simulating(More)
Knowledge on primary processing of sound by the human auditory system has tremendously increased. This paper exploits the opportunities this creates for assessing the impact of (unwanted) environmental noise on quality of life of people. In particular the effect of auditory attention in a multisource context is focused on. The typical application envisaged(More)
It has been stated frequently that the soundscape as perceived and appraised by the user of a space, extends beyond the physical stimulus. We argue that, when introducing to human-factor in analyzing a sonic environment, the sounds that people hear play an important role. This holds in particular for rather quiet and infrequent disturbance of park(More)
A classification algorithm for environmental sound recordings or ldquosoundscapesrdquo is outlined. An ant clustering approach is proposed, in which the behavior of the ants is governed by fuzzy rules. These rules are optimized by a genetic algorithm specially designed in order to achieve the optimal set of homogeneous clusters. Soundscape similarity is(More)
In this paper, the use of fuzzy ant clustering in classifying a large database of environmental soundscape recordings is outlined. Fuzzy ant clustering is a soft computing technique inspired by the clustering behaviour observed in colonies of several ant species. Virtual ants or “agents” move through the database, “pick up” soundscape recordings and drop(More)