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Source Separation
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
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DOI
arXiv
GitHub
ICLR 2024 notable top 1.2% (oral)
Generalized Multi-Source Inference for Text Conditioned Music Diffusion Models
Multi-Source Diffusion Models (MSDM) allow for compositional musical generation tasks: generating a set of coherent sources, creating …
Emilian Postolache
,
Giorgio Mariani
,
Emmanouil Benetos
,
Luca Cosmo
,
Emanuele Rodolà
Cite
arXiv
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
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
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