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Towards Solving Cocktail-Party: The First Method to Build a Realistic
  Dataset with Ground Truths for Speech Separation

Towards Solving Cocktail-Party: The First Method to Build a Realistic Dataset with Ground Truths for Speech Separation

25 May 2023
Rawad Melhem
Assef Jafar
Oumayma Al Dakkak
ArXivPDFHTML

Papers citing "Towards Solving Cocktail-Party: The First Method to Build a Realistic Dataset with Ground Truths for Speech Separation"

4 / 4 papers shown
Title
TF-GridNet: Making Time-Frequency Domain Models Great Again for Monaural
  Speaker Separation
TF-GridNet: Making Time-Frequency Domain Models Great Again for Monaural Speaker Separation
Zhong-Qiu Wang
Samuele Cornell
Shukjae Choi
Younglo Lee
Byeonghak Kim
Shinji Watanabe
74
96
0
08 Sep 2022
Remix-cycle-consistent Learning on Adversarially Learned Separator for
  Accurate and Stable Unsupervised Speech Separation
Remix-cycle-consistent Learning on Adversarially Learned Separator for Accurate and Stable Unsupervised Speech Separation
Kohei Saijo
Tetsuji Ogawa
18
9
0
26 Mar 2022
Training Noisy Single-Channel Speech Separation With Noisy Oracle
  Sources: A Large Gap and A Small Step
Training Noisy Single-Channel Speech Separation With Noisy Oracle Sources: A Large Gap and A Small Step
Matthew Maciejewski
Jing Shi
Shinji Watanabe
Sanjeev Khudanpur
18
11
0
23 Oct 2020
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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