6 papers
A Fast Solver for Interpolating Stochastic Differential Equation Diffusion Models for Speech Restoration
Bunlong Lay, Timo Gerkmann
Diffusion Probabilistic Models (DPMs) are a well-established class of diffusion models for unconditional image generation, while SGMSE+ is a well-established conditional diffusion…
Real-Time Streamable Generative Speech Restoration with Flow Matching
Simon Welker, Bunlong Lay, Maris Hillemann +2
Diffusion-based generative models have greatly impacted the speech processing field in recent years, exhibiting high speech naturalness and spawning a new research direction. Their…
Bone-conduction Guided Multimodal Speech Enhancement with Conditional Diffusion Models
Sina Khanagha, Bunlong Lay, Timo Gerkmann
Single-channel speech enhancement models face significant performance degradation in extremely noisy environments. While prior work has shown that complementary bone-conducted spee…
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…
Speech Enhancement and Dereverberation with Diffusion-based Generative Models
Julius Richter, Simon Welker, Jean-Marie Lemercier +2
In this work, we build upon our previous publication and use diffusion-based generative models for speech enhancement. We present a detailed overview of the diffusion process that…
Diffusion Buffer: Online Diffusion-based Speech Enhancement with Sub-Second Latency
Bunlong Lay, Rostislav Makarov, Timo Gerkmann
Diffusion models are a class of generative models that have been recently used for speech enhancement with remarkable success but are computationally expensive at inference time. T…