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Found 3 papers, 1 papers with code
HD-DEMUCS: General Speech Restoration with Heterogeneous Decoders
This paper introduces an end-to-end neural speech restoration model, HD-DEMUCS, demonstrating efficacy across multiple distortion environments.
An empirical study on speech restoration guided by self supervised speech representation
Our experiments demonstrate that the contextual information provided by the self-supervised speech representation can enhance speech restoration performance in various distortion scenarios, while also increasing robustness against the duration of speech attenuation and mismatched test conditions.
Diffusion-based Generative Speech Source Separation
We propose DiffSep, a new single channel source separation method based on score-matching of a stochastic differential equation (SDE).
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