68 citations · 87 across the 5 of their papers we have counts for
5 papers
Integrating Uncertainty into Neural Network-based Speech Enhancement
Huajian Fang, Dennis Becker, Stefan Wermter +1
Supervised masking approaches in the time-frequency domain aim to employ deep neural networks to estimate a multiplicative mask to extract clean speech. This leads to a single esti…
Partially Adaptive Multichannel Joint Reduction of Ego-noise and Environmental Noise
Huajian Fang, Niklas Wittmer, Johannes Twiefel +2
Human-robot interaction relies on a noise-robust audio processing module capable of estimating target speech from audio recordings impacted by environmental noise, as well as self-…
Uncertainty Estimation in Deep Speech Enhancement Using Complex Gaussian Mixture Models
Huajian Fang, Timo Gerkmann
Single-channel deep speech enhancement approaches often estimate a single multiplicative mask to extract clean speech without a measure of its accuracy. Instead, in this work, we p…
Integrating Statistical Uncertainty into Neural Network-Based Speech Enhancement
Huajian Fang, Tal Peer, Stefan Wermter +1
Speech enhancement in the time-frequency domain is often performed by estimating a multiplicative mask to extract clean speech. However, most neural network-based methods perform p…
Variational Autoencoder for Speech Enhancement with a Noise-Aware Encoder
Huajian Fang, Guillaume Carbajal, Stefan Wermter +1
Recently, a generative variational autoencoder (VAE) has been proposed for speech enhancement to model speech statistics. However, this approach only uses clean speech in the train…