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Two-Step Sound Source Separation: Training on Learned Latent Targets
Efthymios Tzinis
, Shrikant Venkataramani
, Zhepei Wang
, Cem Subakan
, Paris Smaragdis
Electrical and Computer Engineering
Coordinated Science Lab
Siebel School of Computing and Data Science
Research output
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Chapter in Book/Report/Conference proceeding
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Conference contribution
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Dive into the research topics of 'Two-Step Sound Source Separation: Training on Learned Latent Targets'. Together they form a unique fingerprint.
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Keyphrases
Scale Invariant
100%
Latent Space
100%
Signal-to-Distortion Ratio
100%
Sound Source Separation
100%
Neural Network
50%
Proposed Methodology
50%
Large Classes
50%
Separation System
50%
Two-stage Training
50%
Loss Function
50%
Separation Performance
50%
Oracle
50%
Source Separation
50%
Training Procedure
50%
Deep Neural Network
50%
Separation Experiment
50%
Sound Separation
50%
Mathematics
Neural Network
100%
Time Domain
100%
Loss Function
100%
Sound Source
100%
Deep Neural Network
100%
Training Procedure
100%
Computer Science
Source Separation
100%
Neural Network
50%
Deep Neural Network
50%
Separation Performance
50%