ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2405.01242
  4. Cited By
TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio
  and Bone Conduction Speech Super Resolution and Enhancement on Mobile and
  Wearable Platforms

TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms

2 May 2024
Yueyuan Sui
Minghui Zhao
Junxi Xia
Xiaofan Jiang
S. Xia
    Mamba
ArXivPDFHTML

Papers citing "TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms"

5 / 5 papers shown
Title
CleanUMamba: A Compact Mamba Network for Speech Denoising using Channel Pruning
CleanUMamba: A Compact Mamba Network for Speech Denoising using Channel Pruning
Sjoerd Groot
Qinyu Chen
Jan C. van Gemert
Chang Gao
Mamba
123
0
0
14 Oct 2024
Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors
Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors
J. Hauret
Malo Olivier
Thomas Joubaud
C. Langrenne
Sarah Poirée
V. Zimpfer
Éric Bavu
75
1
0
16 Jul 2024
Speech Slytherin: Examining the Performance and Efficiency of Mamba for
  Speech Separation, Recognition, and Synthesis
Speech Slytherin: Examining the Performance and Efficiency of Mamba for Speech Separation, Recognition, and Synthesis
Xilin Jiang
Yinghao Aaron Li
Adrian Nicolas Florea
Cong Han
N. Mesgarani
Mamba
38
9
0
13 Jul 2024
SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
Siavash Shams
Sukru Samet Dindar
Xilin Jiang
N. Mesgarani
Mamba
64
18
0
20 May 2024
Real-Time Single Image and Video Super-Resolution Using an Efficient
  Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
190
5,173
0
16 Sep 2016
1