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Source Separation
Latent Autoregressive Source Separation
Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task …
Emilian Postolache
,
Giorgio Mariani
,
Michele Mancusi
,
Andrea Santilli
,
Luca Cosmo
,
Emanuele Rodolà
Cite
arXiv
GitHub
Multi-Source Diffusion Models for Simultaneous Music Generation and Separation
In this work, we define a diffusion-based generative model capable of both music synthesis and source separation by learning the score …
Giorgio Mariani
,
Irene Tallini
,
Emilian Postolache
,
Michele Mancusi
,
Luca Cosmo
,
Emanuele Rodolà
Cite
DOI
arXiv
GitHub
Adversarial Permutation Invariant Training for Universal Sound Separation
Universal sound separation consists of separating mixes with arbitrary sounds of different types, and permutation invariant training …
Emilian Postolache
,
Jordi Pons
,
Santiago Pascual
,
Joan Serrà
Cite
arXiv
Unsupervised source separation via Bayesian inference in the latent domain
State of the art audio source separation models rely on supervised data-driven approaches, which can be expensive in terms of labeling …
Michele Mancusi
,
Emilian Postolache
,
Giorgio Mariani
,
Marco Fumero
,
Andrea Santilli
,
Luca Cosmo
,
Emanuele Rodolà
Cite
arXiv
GitHub
Cite
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