May 15, 2023 · The proposed approach captures aleatoric uncertainty by estimating the statistical moments of the speech posterior distribution and explicitly ...

Integrating Uncertainty into Neural Network-based Speech Enhancement. This repository contains the code for the paper: Huajian Fang, Dennis Becker, Stefan ...

In this work, we propose a framework to jointly model aleatoric and epistemic uncertainties in neural network-based speech enhancement. The proposed approach.

Dec 9, 2024 · In this work, we propose a framework to jointly model aleatoric and epistemic uncertainties in neural network-based speech enhancement. The ...

In this paper, we study the benefits of modeling uncertainty in neural network-based speech enhancement. For this, our neural network is trained to map a noisy ...

In this work, we propose a framework to jointly model aleatoric and epistemic uncertainties in neural network-based speech enhancement. The proposed approach ...

May 15, 2023 · In this work, we propose a framework to jointly model aleatoric and epistemic uncertainties in neural network-based speech enhancement. The ...

Experimental results show that the proposed method can not only capture the uncertainty associated with the estimated filters, but also yield a higher ...

The proposed framework captures aleatoric uncertainty by estimating the statistical moments of the speech posterior distribution and explicitly incorporates ...

In this paper, we study the benefits of modeling uncertainty in neural network-based speech enhancement. For this, our neural network is trained to map a noisy.