Machine listening and auditory cognition
Competences:
- 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
Collaborations:
- 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: