Gabor Frames and Deep Scattering Networks in Audio Processing

This paper introduces Gabor scattering, a feature extractor based on Gabor frames and Mallat’s scattering transform. By using a simple signal model for audio signals, specific properties of Gabor scattering are studied. It is shown that, for each layer, specific invariances to certain sign...

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Bibliographic Details
Main Authors: Roswitha Bammer, Monika Dörfler, Pavol Harar
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Axioms
Subjects:
Online Access:https://www.mdpi.com/2075-1680/8/4/106
Description
Summary:This paper introduces Gabor scattering, a feature extractor based on Gabor frames and Mallat’s scattering transform. By using a simple signal model for audio signals, specific properties of Gabor scattering are studied. It is shown that, for each layer, specific invariances to certain signal characteristics occur. Furthermore, deformation stability of the coefficient vector generated by the feature extractor is derived by using a decoupling technique which exploits the contractivity of general scattering networks. Deformations are introduced as changes in spectral shape and frequency modulation. The theoretical results are illustrated by numerical examples and experiments. Numerical evidence is given by evaluation on a synthetic and a “real” dataset, that the invariances encoded by the Gabor scattering transform lead to higher performance in comparison with just using Gabor transform, especially when few training samples are available.
ISSN:2075-1680