176 citations · 195 across the 12 of their papers we have counts for
3 papers · 2 filters
Learning Filterbanks for End-to-End Acoustic Beamforming
Samuele Cornell, Manuel Pariente, François Grondin +1
Recent work on monaural source separation has shown that performance can be increased by using fully learned filterbanks with short windows. On the other hand it is widely known th…
Deep Optimization of Parametric IIR Filters for Audio Equalization
Giovanni Pepe, Leonardo Gabrielli, Stefano Squartini +2
This paper describes a novel Deep Learning method for the design of IIR parametric filters for automatic audio equalization. A simple and effective neural architecture, named BiasN…
Learning to Rank Microphones for Distant Speech Recognition
Samuele Cornell, Alessio Brutti, Marco Matassoni +1
Fully exploiting ad-hoc microphone networks for distant speech recognition is still an open issue. Empirical evidence shows that being able to select the best microphone leads to s…