Machine listening and auditory cognition

  • Application and development of computational models (neural networks and deep learning models) for auditory perception, sound classification and identification.
  • Disentangling auditory attention using single-trial electroencephalography (EEG).
  • Modelling the perceived quality of outdoor soundscapes, based on holistic perceptual indicators, as well as the presence of particular sounds and their associated meaning.
  • Modelling the emergence of noise annoyance due to combined noise sources.
  • Application of models for machine listening and auditory cognition into smart sound meters and acoustic sensor networks.

Research projects: 
  • FWO postdoctoral fellowship Bert De Coensel
  • FWO doctoral fellowship Michiel Boes
  • Marie Curie ITN Sonorus
  • FWO ERC Runner-up project MAESTRO
  • UGent BOF DUCK project
  • Department of Experimental Psychology, Ghent University
  • Gösta Ekman Laboratory for Sensory Research, Stockholm University, Sweden
  • BRAMS (International Laboratory for Brain, Music and Sound Research), University of Montreal, Canada
  • Auditory Neuroscience Laboratory, Boston University, USA
  • ASAsense
Tools and Valorisation: 

ASAsense is a spin-off company of the WAVES lab, that develops and deploys smart sensor network solutions.

Key Publications: