7 citations · 16 across the 6 of their papers we have counts for
4 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…
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…
Adaptive Slimming for Scalable and Efficient Speech Enhancement
Riccardo Miccini, Minje Kim, Clément Laroche +2
Speech enhancement (SE) enables robust speech recognition, real-time communication, hearing aids, and other applications where speech quality is crucial. However, deploying such sy…
Scalable Speech Enhancement with Dynamic Channel Pruning
Riccardo Miccini, Clement Laroche, Tobias Piechowiak +1
Speech Enhancement (SE) is essential for improving productivity in remote collaborative environments. Although deep learning models are highly effective at SE, their computational…