1 citations · 2 across the 4 of their papers we have counts for
4 papers
It Takes Few to TANGO: A Quantized Distributed Model for Binaural Speech Enhancement
Zahra Benslimane, Pierre Chouteau, Martyna Poreba +4
Neural network-based multichannel speech enhancement systems achieve strong enhancement performance, but their computational and memory requirements limit deployment on resource-co…
RT-Tango: Real-Time Distributed Binaural Speech Enhancement for Low-Power Hearing Aid Devices
Z. Benslimane, P. Chouteau, M. Poreba +4
Real-time binaural speech enhancement is constrained by latency, computational cost, and inter-device communication, yet existing efficient solutions predominantly address single-c…
When Conventional machine learning meets neuromorphic engineering: Deep Temporal Networks (DTNets) a machine learning frawmework allowing to operate on Events and Frames and implantable on Tensor Flow Like Hardware
Marco Macanovic, Fabian Chersi, Felix Rutard +2
We introduce in this paper the principle of Deep Temporal Networks that allow to add time to convolutional networks by allowing deep integration principles not only using spatial i…
The hippocampal-striatal circuit for goal-directed and habitual choice
Fabian Chersi
It is now widely accepted that one of the roles of the hippocampus is to maintain episodic spatial representations, while parallel striatal pathways contribute to both declarative…