Guochen Yu

Orcid: 0000-0002-7179-1044

According to our database1, Guochen Yu authored at least 23 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Links

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Bibliography

2024
TaBE: Decoupling spatial and spectral processing with Taylor's unfolding method in the beamspace domain for multi-channel speech enhancement.
Inf. Fusion, January, 2024

KS-Net: Multi-band joint speech restoration and enhancement network for 2024 ICASSP SSI Challenge.
CoRR, 2024

2023
A General Unfolding Speech Enhancement Method Motivated by Taylor's Theorem.
IEEE ACM Trans. Audio Speech Lang. Process., 2023

BAE-Net: A Low complexity and high fidelity Bandwidth-Adaptive neural network for speech super-resolution.
CoRR, 2023

Hybrid TOA/AOA Indoor Positioning Based on Sparse Reconstruction and Map Matching.
Proceedings of the 98th IEEE Vehicular Technology Conference, 2023

2022
DBT-Net: Dual-Branch Federative Magnitude and Phase Estimation With Attention-in-Attention Transformer for Monaural Speech Enhancement.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

Filtering and Refining: A Collaborative-Style Framework for Single-Channel Speech Enhancement.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

A General Deep Learning Speech Enhancement Framework Motivated by Taylor's Theorem.
CoRR, 2022

TaylorBeamixer: Learning Taylor-Inspired All-Neural Multi-Channel Speech Enhancement from Beam-Space Dictionary Perspective.
CoRR, 2022

Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Band Speech Enhancement.
CoRR, 2022

DMF-Net: A decoupling-style multi-band fusion model for real-time full-band speech enhancement.
CoRR, 2022

Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Full-Band Speech Enhancement.
Proceedings of the 13th International Symposium on Chinese Spoken Language Processing, 2022

TaylorBeamformer: Learning All-Neural Beamformer for Multi-Channel Speech Enhancement from Taylor's Approximation Theory.
Proceedings of the Interspeech 2022, 2022

TMGAN-PLC: Audio Packet Loss Concealment using Temporal Memory Generative Adversarial Network.
Proceedings of the Interspeech 2022, 2022

Taylor, Can You Hear Me Now? A Taylor-Unfolding Framework for Monaural Speech Enhancement.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Low Complexity DOA Estimation Algorithms Based on Propagator for Massive MIMO Systems.
Proceedings of the 22nd IEEE International Conference on Communication Technology, 2022

Dual-Branch Attention-In-Attention Transformer for Single-Channel Speech Enhancement.
Proceedings of the IEEE International Conference on Acoustics, 2022

Joint Magnitude Estimation and Phase Recovery Using Cycle-In-Cycle GAN for Non-Parallel Speech Enhancement.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
A two-stage complex network using cycle-consistent generative adversarial networks for speech enhancement.
Speech Commun., 2021

Joint magnitude estimation and phase recovery using Cyle-in-cycle GAN for non-parallel speech enhancement.
CoRR, 2021

A Simultaneous Denoising and Dereverberation Framework with Target Decoupling.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

CycleGAN-based Non-parallel Speech Enhancement with an Adaptive Attention-in-attention Mechanism.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2021

2020
Improved Relativistic Cycle-Consistent GAN With Dilated Residual Network and Multi-Attention for Speech Enhancement.
IEEE Access, 2020


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