4 papers
Livin' on a Prior: Likelihood Score Approximation for Inverse Problems
Rostislav Makarov, Tal Peer, Danilo de Oliveira +1
Generative models have found great success as data-driven methods of solving inverse problems. Two popular approaches work either by combining a pretrained generative prior with a…
Repurposing a Speech Classifier for Guided Diffusion-Based Speech Generation
Rostislav Makarov, Timo Gerkmann
Classifier guidance is a way to control diffusion generation by using a noise-conditioned classifier to steer the sampling process toward a target class. One drawback of classifier…
Diffusion Buffer for Online Generative Speech Enhancement
Bunlong Lay, Rostislav Makarov, Simon Welker +2
Online Speech Enhancement was mainly reserved for predictive models. A key advantage of these models is that for an incoming signal frame from a stream of data, the model is called…
Are Modern Speech Enhancement Systems Vulnerable to Adversarial Attacks?
Rostislav Makarov, Lea Schönherr, Timo Gerkmann
Machine learning approaches for speech enhancement are becoming increasingly expressive, enabling ever more powerful modifications of input signals. In this paper, we demonstrate t…