The simultaneous denoising and dereverberation for single-channel mixture speech under
the complicated acoustic environment is considered to be a challengeable task. In this …

We propose a joint progressive learning (JPL) framework of gradually mapping highly noisy
and reverberant speech features to less noisy and less reverberant speech features in a …

Monaural speech dereverberation is a very challenging task because no spatial cues can be
used. When the additive noises exist, this task becomes more challenging. In this paper, we …

Monaural speech dereverberation is a very challenging task because no spatial cues can be
used. When the additive noises exist, this task becomes more challenging. In this paper, we …

Recently, many Transformer-style dual-path models have achieved impressive performance
for speech enhancement. However, their high parameters and computational complexity …

In this work, we tackle a denoising and dereverberation problem with a single-stage
framework. Although denoising and dereverberation may be considered two separate …

In this paper, we propose a multi-channel network for simultaneous speech dereverberation,
enhancement and separation (DESNet). To enable gradient propagation and joint …

Background noise and room reverberation are regarded as two major factors to degrade the
subjective speech quality. In this paper, we propose an integrated framework to address …

This work proposes a neural network to extensively exploit spatial information for
multichannel joint speech separation, denoising and dereverberation, named SpatialNet. In …

Complex spectrum and magnitude are considered as two major features of speech
enhancement and dereverberation. Traditional approaches always treat these two features …