Search Results for author:
Found 6 papers, 2 papers with code
GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration
Pre-trained diffusion models have been successfully used as priors in a variety of linear inverse problems, where the goal is to reconstruct a signal from noisy linear measurements.
Sampling-Frequency-Independent Audio Source Separation Using Convolution Layer Based on Impulse Invariant Method
Audio source separation is often used as preprocessing of various applications, and one of its ultimate goals is to construct a single versatile model capable of dealing with the varieties of audio signals.
U(1) spin Chern-Simons theory and Arf invariants in two dimensions
We use the modular matrices to calculate the partition function of the spin Chern-Simons theory on the lens space $L(a,\pm 1)$, and demonstrate the expected dependence on the 3d spin structure.
High Energy Physics - Theory Strongly Correlated Electrons
Training Speech Enhancement Systems with Noisy Speech Datasets
Furthermore, we propose a noise augmentation scheme for mixture-invariant training (MixIT), which allows using it also in such scenarios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Unsupervised vocal dereverberation with diffusion-based generative models
Removing reverb from reverberant music is a necessary technique to clean up audio for downstream music manipulations.
VRDMG: Vocal Restoration via Diffusion Posterior Sampling with Multiple Guidance
Restoring degraded music signals is essential to enhance audio quality for downstream music manipulation.
