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MUSE: Flexible Voiceprint Receptive Fields and Multi-Path Fusion
  Enhanced Taylor Transformer for U-Net-based Speech Enhancement

MUSE: Flexible Voiceprint Receptive Fields and Multi-Path Fusion Enhanced Taylor Transformer for U-Net-based Speech Enhancement

7 June 2024
Zizhen Lin
Xiaoting Chen
Junyu Wang
ArXivPDFHTML

Papers citing "MUSE: Flexible Voiceprint Receptive Fields and Multi-Path Fusion Enhanced Taylor Transformer for U-Net-based Speech Enhancement"

3 / 3 papers shown
Title
DPT-FSNet: Dual-path Transformer Based Full-band and Sub-band Fusion
  Network for Speech Enhancement
DPT-FSNet: Dual-path Transformer Based Full-band and Sub-band Fusion Network for Speech Enhancement
Feng Dang
Hangting Chen
Pengyuan Zhang
65
94
0
27 Apr 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,214
0
17 Apr 2017
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
229
74,467
0
18 May 2015
1