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Building a great multi-lingual teacher with sparsely-gated mixture of
  experts for speech recognition

Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition

10 December 2021
K. Kumatani
R. Gmyr
Andres Felipe Cruz Salinas
Linquan Liu
Wei Zuo
Devang Patel
Eric Sun
Yu Shi
    MoE
ArXivPDFHTML

Papers citing "Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition"

6 / 6 papers shown
Title
Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design
Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design
Mohan Zhang
Pingzhi Li
Jie Peng
Mufan Qiu
Tianlong Chen
MoE
45
0
0
02 Apr 2025
Tight Clusters Make Specialized Experts
Tight Clusters Make Specialized Experts
Stefan K. Nielsen
R. Teo
Laziz U. Abdullaev
Tan M. Nguyen
MoE
66
2
0
21 Feb 2025
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
R. Teo
Tan M. Nguyen
MoE
33
3
0
18 Oct 2024
MoEC: Mixture of Expert Clusters
MoEC: Mixture of Expert Clusters
Yuan Xie
Shaohan Huang
Tianyu Chen
Furu Wei
MoE
40
11
0
19 Jul 2022
Multilingual Speech Recognition using Knowledge Transfer across Learning
  Processes
Multilingual Speech Recognition using Knowledge Transfer across Learning Processes
Rimita Lahiri
K. Kumatani
Eric Sun
Yao Qian
52
6
0
15 Oct 2021
A Configurable Multilingual Model is All You Need to Recognize All
  Languages
A Configurable Multilingual Model is All You Need to Recognize All Languages
Long Zhou
Jinyu Li
Eric Sun
Shujie Liu
92
40
0
13 Jul 2021
1