6 citations · 10 across the 10 of their papers we have counts for
4 papers · 1 filter
ISAC: An Invertible and Stable Auditory Filter Bank with Customizable Kernels for ML Integration
Daniel Haider, Felix Perfler, Peter Balazs +2
This paper introduces ISAC, an invertible and stable, perceptually-motivated filter bank that is specifically designed to be integrated into machine learning paradigms. More precis…
Hold Me Tight: Stable Encoder-Decoder Design for Speech Enhancement
Daniel Haider, Felix Perfler, Vincent Lostanlen +2
Convolutional layers with 1-D filters are often used as frontend to encode audio signals. Unlike fixed time-frequency representations, they can adapt to the local characteristics o…
Fitting Auditory Filterbanks with Multiresolution Neural Networks
Vincent Lostanlen, Daniel Haider, Han Han +3
Waveform-based deep learning faces a dilemma between nonparametric and parametric approaches. On one hand, convolutional neural networks (convnets) may approximate any linear time-…
Phase-Based Signal Representations for Scattering
Daniel Haider, Peter Balazs, Nicki Holighaus
The scattering transform is a non-linear signal representation method based on cascaded wavelet transform magnitudes. In this paper we introduce phase scattering, a novel approach…