Two heads are better than one: A two-stage complex spectral map** approach for monaural speech enhancement
For challenging acoustic scenarios as low signal-to-noise ratios, current speech
enhancement systems usually suffer from performance bottleneck in extracting the target …
enhancement systems usually suffer from performance bottleneck in extracting the target …
ADL-MVDR: All deep learning MVDR beamformer for target speech separation
Speech separation algorithms are often used to separate the target speech from other
interfering sources. However, purely neural network based speech separation systems often …
interfering sources. However, purely neural network based speech separation systems often …
Dual-branch attention-in-attention transformer for single-channel speech enhancement
Curriculum learning begins to thrive in the speech enhancement area, which decouples the
original spectrum estimation task into multiple easier sub-tasks to achieve better …
original spectrum estimation task into multiple easier sub-tasks to achieve better …
Revisiting denoising diffusion probabilistic models for speech enhancement: Condition collapse, efficiency and refinement
Recent literature has shown that denoising diffusion probabilistic models (DDPMs) can be
used to synthesize high-fidelity samples with a competitive (or sometimes better) quality than …
used to synthesize high-fidelity samples with a competitive (or sometimes better) quality than …
DBT-Net: Dual-branch federative magnitude and phase estimation with attention-in-attention transformer for monaural speech enhancement
The decoupling-style concept begins to ignite in the speech enhancement area, which
decouples the original complex spectrum estimation task into multiple easier sub-tasks (ie …
decouples the original complex spectrum estimation task into multiple easier sub-tasks (ie …
Deepresgru: residual gated recurrent neural network-augmented kalman filtering for speech enhancement and recognition
With the recent research developments, deep learning models are powerful alternatives for
speech enhancement and recognition in many real-world applications. Although state-of-the …
speech enhancement and recognition in many real-world applications. Although state-of-the …
Multi-channel multi-frame ADL-MVDR for target speech separation
Many purely neural network based speech separation approaches have been proposed to
improve objective assessment scores, but they often introduce nonlinear distortions that are …
improve objective assessment scores, but they often introduce nonlinear distortions that are …
Self-attention generative adversarial network for speech enhancement
Existing generative adversarial networks (GANs) for speech enhancement solely rely on the
convolution operation, which may obscure temporal dependencies across the sequence …
convolution operation, which may obscure temporal dependencies across the sequence …
A General Unfolding Speech Enhancement Method Motivated by Taylor's Theorem
While deep neural networks have facilitated significant advancements in the field of speech
enhancement, most existing methods are developed following either empirical or relatively …
enhancement, most existing methods are developed following either empirical or relatively …
Exploring self-attention mechanisms for speech separation
Transformers have enabled impressive improvements in deep learning. They often
outperform recurrent and convolutional models in many tasks while taking advantage of …
outperform recurrent and convolutional models in many tasks while taking advantage of …