Individualized Conditioning and Negative Distances for Speaker Separation-Reference-Cited by-同舟云学术

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Individualized Conditioning and Negative Distances for Speaker Separation

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)
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Author:

Sun Tao¹,Abuhajar Nidal¹,Gong Shuyu¹,Wang Zhewei²,Smith Charles D.³,Wang Xianhui⁴,Xu Li⁴,Liu Jundong¹

Affiliation:

1. Ohio University,School of Electrical Engineering and Computer Science,Athens,OH,45701

2. Massachusetts General Hospital,Boston,MA,02114

3. University of Kentucky,Department of Neurology,Lexington,KY,40536

4. Ohio University,Division of Communication Sciences,Athens,OH,45701

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10068862/10068777/10069076.pdf?arnumber=10069076

Reference39 articles.

1. Conv-TasNet: Surpassing Ideal Time–Frequency Magnitude Masking for Speech Separation

2. Librimix: An open-source dataset for generalizable speech separation;cosentino,2020

3. Dilated FCN: Listening Longer to Hear Better

4. Attention Is All You Need In Speech Separation

5. Boosting the Intelligibility of Waveform Speech Enhancement Networks through Self-supervised Representations

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Two-Stage Audio-Visual Speech Separation Method Without Visual Signals for Testing and Tuples Loss With Dynamic Margin;IEEE Journal of Selected Topics in Signal Processing;2024-04

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