Joint Time-Frequency Scattering for Audio Classification
Sound
2018-08-06 v1
Abstract
We introduce the joint time-frequency scattering transform, a time shift invariant descriptor of time-frequency structure for audio classification. It is obtained by applying a two-dimensional wavelet transform in time and log-frequency to a time-frequency wavelet scalogram. We show that this descriptor successfully characterizes complex time-frequency phenomena such as time-varying filters and frequency modulated excitations. State-of-the-art results are achieved for signal reconstruction and phone segment classification on the TIMIT dataset.
Cite
@article{arxiv.1512.02125,
title = {Joint Time-Frequency Scattering for Audio Classification},
author = {Joakim Andén and Vincent Lostanlen and Stéphane Mallat},
journal= {arXiv preprint arXiv:1512.02125},
year = {2018}
}
Comments
6 pages, 2 figures in IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015. Sept. 17-20. Boston, USA