Probabilistic Modelling of Signal Mixtures with Differentiable Dictionaries
Audio and Speech Processing
2022-11-29 v1 Machine Learning
Sound
Abstract
We introduce a novel way to incorporate prior information into (semi-) supervised non-negative matrix factorization, which we call differentiable dictionary search. It enables general, highly flexible and principled modelling of mixtures where non-linear sources are linearly mixed. We study its behavior on an audio decomposition task, and conduct an extensive, highly controlled study of its modelling capabilities.
Keywords
Cite
@article{arxiv.2211.15439,
title = {Probabilistic Modelling of Signal Mixtures with Differentiable Dictionaries},
author = {Lukáš Samuel Marták and Rainer Kelz and Gerhard Widmer},
journal= {arXiv preprint arXiv:2211.15439},
year = {2022}
}
Comments
Published in the Proceedings of the 29th European Signal Processing Conference (EUSIPCO 2021), Dublin, Ireland, August 23-27, 2021 (IEEE), 441-445