41 citations · 95 across the 10 of their papers we have counts for
10 papers
AugCodec: A Low-Bitrate Disentangled Neural Speech Codec via Data Augmentation
Dongmei Wang, Xiaohang Sun, Yang Liu +10
We propose AugCodec, a low-bitrate disentangled neural speech codec that leverages data augmentation to decompose speech into three distinct components: semantic, speaker, and pros…
ConSA: Controllable Sparsity in Hybrid Attention via Learnable Allocation
Yao Chen, Yinqi Yang, Junyuan Shang +6
Hybrid architectures combining full attention (FA) and sliding-window attention (SWA) are a promising paradigm for efficient LLM inference. However, existing methods typically rely…
Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge
Mingshuai Liu, Shubo Lv, Zihan Zhang +6
In ICASSP 2023 speech signal improvement challenge, we developed a dual-stage neural model which improves speech signal quality induced by different distortions in a stage-wise div…
Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech Enhancement
Xiang Hao, Xiaofei Li
FullSubNet is our recently proposed real-time single-channel speech enhancement network that achieves outstanding performance on the Deep Noise Suppression (DNS) Challenge dataset.…
Coarse-to-Fine Recursive Speech Separation for Unknown Number of Speakers
Zhenhao Jin, Xiang Hao, Xiangdong Su
The vast majority of speech separation methods assume that the number of speakers is known in advance, hence they are specific to the number of speakers. By contrast, a more realis…
UNetGAN: A Robust Speech Enhancement Approach in Time Domain for Extremely Low Signal-to-noise Ratio Condition
Xiang Hao, Xiangdong Su, Zhiyu Wang +2
Speech enhancement at extremely low signal-to-noise ratio (SNR) condition is a very challenging problem and rarely investigated in previous works. This paper proposes a robust spee…
FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement
Xiang Hao, Xiangdong Su, Radu Horaud +1
This paper proposes a full-band and sub-band fusion model, named as FullSubNet, for single-channel real-time speech enhancement. Full-band and sub-band refer to the models that inp…
An Edge Information and Mask Shrinking Based Image Inpainting Approach
Huali Xu, Xiangdong Su, Meng Wang +2
In the image inpainting task, the ability to repair both high-frequency and low-frequency information in the missing regions has a substantial influence on the quality of the resto…
SNR-Based Teachers-Student Technique for Speech Enhancement
Xiang Hao, Xiangdong Su, Zhiyu Wang +3
It is very challenging for speech enhancement methods to achieves robust performance under both high signal-to-noise ratio (SNR) and low SNR simultaneously. In this paper, we propo…
Sub-Band Knowledge Distillation Framework for Speech Enhancement
Xiang Hao, Shixue Wen, Xiangdong Su +3
In single-channel speech enhancement, methods based on full-band spectral features have been widely studied. However, only a few methods pay attention to non-full-band spectral fea…