4 accepted papers
Diffusion-based denoising models have demonstrated impressive performance in probabilistic forecasting for multivariate time series (MTS). Nonetheless, existing approaches often model the entire data distribution, neglecting the variability in uncertainty across different components of the time seri…
This paper introduces the SWANT team’s entry to the ICASSP 2023 AEC Challenge. We submit a system that cascades a linear filter with a neural post-filter. Particularly, we adopt sub-band processing to handle full-band signals and shape the network with multi-task learning, where dual signal voice ac…
This paper described the PCG-AIID system for L3DAS22 challenge in Task 1: 3D speech enhancement in office reverberant environment. We proposed a two-stage framework to address multi-channel speech denoising and dereverberation. In the first stage, a multiple input and multiple out-put (MIMO) network…
Research on single channel speech enhancement (SE) has a long tradition, but two main practical problems still remain unsolved. Firstly, it’s hard to balance between enhancement quality and computational efficiency, and low-latency always brings loss of quality. Secondly, enhancement in specific sce…