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Found 2 papers, 2 papers with code
MixCycle: Unsupervised Speech Separation via Cyclic Mixture Permutation Invariant Training
We compare our methods to common supervised and unsupervised baselines: permutation invariant training with dynamic mixing (PIT-DM) and mixture invariant training (MixIT).
Audio Source Separation Using Variational Autoencoders and Weak Class Supervision
In this paper, we propose a source separation method that is trained by observing the mixtures and the class labels of the sources present in the mixture without any access to isolated sources.
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