Vocational training - From machine learning to deep learning -
Grenoble-INP (2 days)
* See here
for more information
Automatic speech processing - PHELMA (Grenoble-INP)
- Lecture 16h + Lab work (4h), more
information here,
(slides available on Chamilo)
Introduction to deep learning - PHELMA (Grenoble-INP)
* Lectures (2h): ConvNet, RNN
(jupiter notebook available on Chamilo)
Fundamentals of Probabilistic Graphical Models - Master 2
MOSIG-SIAM (UGA)
* Lecture (2x1h30): Hidden Markov models
* Lab work (1h30): Practical application of an
HMM-based acoustic-phonetic decoder (slides available on Chamilo)
Bayesian methods for data image analysis - Master 2 SIGMA (UGA)
- Lecture (2x2h): Gaussian Mixture models, Hidden-Markov model,
application to automatic speech recognition (slides
here)
Real-time audio signal processing - PHELMA (Grenoble-INP)
* Lectures (2x2h) : (slides
here)
* Lab work (4*4h) : implementation of a real-time convolution
reverb (audio effect) (sujet
ici) / (ressources
ici)