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Jean Rouat: Neuro-computational signal processing

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What
  • Seminar
When Mar 18, 2013
from 04:30 PM to 06:00 PM
Where A-832, New Music Building, 527 Sherbrooke Street West.
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ABSTRACT

Prof. Rouat will first discuss some characteristics of the brain in relation to information processing and neural computation. He will then bridge these characteristics and discuss some of the implications in signal processing for audible or visual signals. He will illustrate using applications and research work being done in the NECOTIS research group for:

  • The design and implementation of sound (speech/music) and image processing systems;
  • Sensorial substitution systems in which images can be used to generate sounds and vice-versa.

He will conclude by introducing some potential extensions to musical and artistic creations.

Keywords: Object based signal processing; robustness to occlusion, missing features, hierarchical organization, sparsity, binding by synchrony, independent component analysis, auditory scene or visual scene analysis, source separation, speech recognition, music generation, object tracking.

 

ABOUT JEAN ROUAT

Jean Rouat holds a master degree in Physics from Univ. de Bretagne, France (1981), an E. & E. master degree in speech coding and speech recognition from Université de Sherbrooke (1984) and an E. & E. Ph.D. in cognitive and statistical speech recognition jointly with Université de Sherbrooke and McGill University (1988). His post-doc has been with the Medical Research Council, Applied Psychological Unit, Cambridge, UK and the Institute of Physiology, Lausanne, Switzerland. He is now with Université de Sherbrooke where he founded the Computational Neuroscience and Intelligent Signal Processing Research group (NECOTIS). He is also adjunct professor in the département de sciences biologiques, Université de Montréal. His research interests are in Neurocomputational Signal Processing to which he is contributing very actively (more than 100 int. Conf. and journal publications). He is an active member of scientific associations (Acoustical Society of America, Int. Speech Communication, IEEE, Int. Neural Networks Society, Association for Research in Otolaryngology, Society for Neurosience and others). He is a senior member of the IEEE and was on the IEEE technical committee on Machine Learning for Signal Processing from 2001 to 2005. 

His current research covers:

  • Substitution from vision to audition through the design of automatic image analysis systems and audible signals synthesis;
  • The substitution from audition to vision through the design of automatic auditory scene analysis systems and image synthesis;
  • The separation and classification of auditory objects;
  • The separation and classification of visual objects;
  • Models of audition and vision;
  • Enhancement of visual or audible signals;
  • Applications in signal classifications (Auditory and visual scenes analysis, Automatic recognition of audible objects for speech/music recognition, Visual object recognition, Electro-neurophysiological signal classification). 

 


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