World leading CEDAR Audio ships improved audio desaturation based on PANAMA’s Sparse Audio Declipper technology
Click here to learn more on the Sparse Audio Declipper: read the papers where it is described and tested; download the corresponding Matlab code; listen to audio examples; test it on your own files from your browser.
Ever faced saturated audio recordings ? Try A-SPADE, the Sparse Audio Declipper.
Clipping, also known as saturation, is a comon phenomenon leading to sometimes seriously distorted audio recordings. Declipping consists in performing the inverse process, to restore saturated audio recordings and improve their quality. A-SPADE is a declipping algorithm developed by PANAMA. It is based on on the expression of declipping as a linear inverse problem and the use of analysis sparse (aka cosparse) regularization in the time-frequency domain.
The PHYSALIS Matlab code allows to reproduce the experiments from a series of papers from our group on cosparse (=analysis flavor of sparse) source localization, for both acoustic inverse problems and EEG inverse problems. It is available here
The CBC4CS code allows to reproduce convex blind calibration experiments in the context of compressive sensing. It is available here.
Tous les détails sur le site de la Journée Sciences et Musiqe, jsm.irisa.fr
(closed) PhD offer – Interactive Navigation for a Video Audio True Experience @ PANAMA, Inria Rennes
Details and appliication here
Congratulations to Antoine Deleforge (new PANAMA team member), Florence Forbes (MISTIS team) and Radu Horaud (PERCEPTION team) who received the 2016 Hojjat Adeli Award for Outstanding Contributions in Neural Systems for their paper:
- A. Deleforge, F. Forbes, and R. Horaud (2015), “Acoustic Space Learning for Sound-source Separation and Localization on Binaural Manifolds,” International Journal of Neural Systems, 25:1, 1440003 (21 pages)
The Award for Outstanding Contributions in Neural Systems established by World Scientific Publishing Co. in 2010, is awarded annually to the most innovative paper published in the previous volume/year of the International Journal of Neural Systems.
For more information concerning this paper please visit the page of the PERCEPTION team on Acoustic Space Learning on Binaural Manifolds (article download, Matlab code, datasets, etc.)
(closed) PhD offer – Estimating the Geometry of Audio Scenes Using Virtually-Supervised Learning @ Inria Rennes
Details and application here