Low complexity speech enhancement network based on frame-level Swin transformer
W Jiang, C Sun, F Chen, Y Leng, Q Guo, J Sun, J Peng - Electronics, 2023 - mdpi.com
In recent years, Transformer has shown great performance in speech enhancement by
applying multi-head self-attention to capture long-term dependencies effectively. However …
applying multi-head self-attention to capture long-term dependencies effectively. However …
A novel speech enhancement method by learnable sparse and low-rank decomposition and domain adaptation
This paper proposes a novel speech enhancement algorithm based on a low-rank sparse
decomposition model. The sparse and low-rank components of a corrupted signal are …
decomposition model. The sparse and low-rank components of a corrupted signal are …
Acquisition and enhancement of remote human vocal signals based on Doppler radar
X Xiang, X Zhang, H Chen - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In order to achieve remote voice acquisition, a 9.75-GHz microwave Doppler radar with a
high-sensitivity coherent homodyne demodulator is used to detect voice signals. However …
high-sensitivity coherent homodyne demodulator is used to detect voice signals. However …
Speech Enhancement Based on Enhanced Empirical Wavelet Transform and Teager Energy Operator
P Kuwałek, W Jęśko - Electronics, 2023 - mdpi.com
This paper presents a new speech-enhancement approach based on an enhanced
empirical wavelet transform, considering the time and scale adaptation of thresholds for …
empirical wavelet transform, considering the time and scale adaptation of thresholds for …
Low-rank and sparsity analysis applied to speech enhancement via online estimated dictionary
P Sun, J Qin - IEEE Signal Processing Letters, 2016 - ieeexplore.ieee.org
In this letter, we propose an online estimated local dictionary based single-channel speech
enhancement algorithm, which focuses on low-rank and sparse matrix decomposition. In the …
enhancement algorithm, which focuses on low-rank and sparse matrix decomposition. In the …
[PDF][PDF] 色噪声下基于白化频谱重排鲁棒主成分分析的语音增强算法
罗勇江， 杨腾飞， 赵冬 - 电子与信息学报, 2021 - jeit.ac.cn
基于鲁棒主成分分析(RPCA) 的单通道语音增强算法是高斯白噪声环境下语音增强的一种重要
处理手段, 但其对低秩语音分量处理效果欠佳且无法较好地抑制色噪声. 针对此问题 …
处理手段, 但其对低秩语音分量处理效果欠佳且无法较好地抑制色噪声. 针对此问题 …
Compressive sampling and data fusion-based structural damage monitoring in wireless sensor network
S Ji, C Tan, P Yang, YJ Sun, D Fu, J Wang - The Journal of …, 2018 - Springer
The Lamb wave phased array structural health monitoring method is effective in structural
damage monitoring. In this method, the damage scattering signal can be obtained by …
damage monitoring. In this method, the damage scattering signal can be obtained by …
Unsupervised speech enhancement in low SNR environments via sparseness and temporal gradient regularization
A crucial stage in unsupervised speech enhancement algorithm is the estimation of noise
related parameters which usually needs prior models for noise. However, estimation of such …
related parameters which usually needs prior models for noise. However, estimation of such …
Single-channel speech enhancement based on adaptive low-rank matrix decomposition
C Li, T Jiang, S Wu, J Xie - IEEE Access, 2020 - ieeexplore.ieee.org
The low-rank matrix decomposition (LMD) algorithm based on the maximum correntropy
criterion (MCC) has recently shown its superiority to other algorithms in classification (eg …
criterion (MCC) has recently shown its superiority to other algorithms in classification (eg …
Deep neural network based supervised speech enhancement in speech-babble noise
Speech enhancement is fundamental for many real-time speech applications and it is
challenging in case of single-channel because practically only one data channel is …
challenging in case of single-channel because practically only one data channel is …