5 citations · 9 across the 5 of their papers we have counts for
3 papers · 1 filter
Does per-frame early exit pay? A compute-matched study of dynamic depth for on-device speech enhancement
Clément Laroche, Riccardo Miccini
Deep learning-based speech enhancement is increasingly deployed on-device in hearing aids, headsets, and earbuds. Most of these devices, however, can only accelerate static int8 gr…
Beyond Model Size: Redesigning LiSenNet for embedded speech enhancement
Clément Laroche, Rasmus Kongsgaard Olsson
Deploying real-time speech enhancement on resource-constrained devices requires meeting strict latency, memory, and energy constraints. Microcontroller NPUs can accelerate neural i…
From Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks
Riccardo Miccini, Clément Laroche, Tobias Piechowiak +2
Speech Enhancement (SE) in audio devices is often supported by auxiliary modules for Voice Activity Detection (VAD), SNR estimation, or Acoustic Scene Classification to ensure robu…