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Towards Listening to 10 People Simultaneously: An Efficient Permutation
  Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm

Towards Listening to 10 People Simultaneously: An Efficient Permutation Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm

22 October 2020
Hideyuki Tachibana
ArXivPDFHTML

Papers citing "Towards Listening to 10 People Simultaneously: An Efficient Permutation Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm"

5 / 5 papers shown
Title
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
David Perera
Victor Letzelter
Théo Mariotte
Adrien Cortés
Mickaël Chen
S. Essid
Ga¨el Richard
74
2
0
20 Jan 2025
Deep neural network techniques for monaural speech enhancement: state of
  the art analysis
Deep neural network techniques for monaural speech enhancement: state of the art analysis
P. Ochieng
30
21
0
01 Dec 2022
Location-based training for multi-channel talker-independent speaker
  separation
Location-based training for multi-channel talker-independent speaker separation
H. Taherian
Ke Tan
DeLiang Wang
27
10
0
08 Oct 2021
Many-Speakers Single Channel Speech Separation with Optimal Permutation
  Training
Many-Speakers Single Channel Speech Separation with Optimal Permutation Training
Shaked Dovrat
Eliya Nachmani
Lior Wolf
VLM
6
21
0
18 Apr 2021
Dual-Path Transformer Network: Direct Context-Aware Modeling for
  End-to-End Monaural Speech Separation
Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation
Jing-jing Chen
Qi-rong Mao
Dong Liu
62
280
0
28 Jul 2020
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