MixCycle: Unsupervised Speech Separation via Cyclic Mixture Permutation Invariant Training
Author:
Affiliation:
1. Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey
2. Department of Electrical and Electronics Engineering, MEF University, Istanbul, Turkey
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/97/9686799/09999309.pdf?arnumber=9999309
Reference27 articles.
1. Unsupervised sound separation using mixture invariant training;wisdom;Proc Adv Neural Inf Process Syst,0
2. Investigating Self-Supervised Learning for Speech Enhancement and Separation
3. Adapting Speech Separation to Real-World Meetings using Mixture Invariant Training
4. Sparse, Efficient, and Semantic Mixture Invariant Training: Taming In-the-Wild Unsupervised Sound Separation
5. Unsupervised Blind Source Separation with Variational Auto-Encoders
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1. Source separation and classification using generative adversarial networks and weak class supervision;Digital Signal Processing;2024-11
2. Deep neural network techniques for monaural speech enhancement and separation: state of the art analysis;Artificial Intelligence Review;2023-10-25
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