An Analysis of the Variance of Diffusion-based Speech Enhancement

Diffusion models proved to be powerful models for generative speech enhancement. In recent SGMSE+ approaches, training involves a stochastic differential equation for the diffusion process, adding both Gaussian and environmental noise to the clean speech signal gradually. The speech enhancement performance varies depending on the choice of the stochastic differential equation that controls the evolution of the mean and the variance along the diffusion processes when adding environmental and Gaussian noise. In this work, we highlight that the scale of …

analysis cs.lg cs.sd differential differential equation diffusion diffusion models eess.as environmental equation generative generative speech noise performance process signal speech stochastic training variance