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Found 16 papers, 7 papers with code
Diffusion Models for Audio Restoration
Here, we aim to show that diffusion models can combine the best of both worlds and offer the opportunity to design audio restoration algorithms with a good degree of interpretability and a remarkable performance in terms of sound quality.
EMOCONV-DIFF: Diffusion-based Speech Emotion Conversion for Non-parallel and In-the-wild Data
Subsequently, at inference, a target emotion embedding is employed to convert the emotion of the input utterance to the given target emotion.
Live Iterative Ptychography with projection-based algorithms
In this work, we demonstrate that the ptychographic phase problem can be solved in a live fashion during scanning, while data is still being collected.
A Flexible Online Framework for Projection-Based STFT Phase Retrieval
Several recent contributions in the field of iterative STFT phase retrieval have demonstrated that the performance of the classical Griffin-Lim method can be considerably improved upon.
Diffusion Posterior Sampling for Informed Single-Channel Dereverberation
We present in this paper an informed single-channel dereverberation method based on conditional generation with diffusion models.
Speech Signal Improvement Using Causal Generative Diffusion Models
In this paper, we present a causal speech signal improvement system that is designed to handle different types of distortions.
Reducing the Prior Mismatch of Stochastic Differential Equations for Diffusion-based Speech Enhancement
Recently, score-based generative models have been successfully employed for the task of speech enhancement.
StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberation
As diffusion models are generative approaches they may also produce vocalizing and breathing artifacts in adverse conditions.
DriftRec: Adapting diffusion models to blind JPEG restoration
In this work, we utilize the high-fidelity generation abilities of diffusion models to solve blind JPEG restoration at high compression levels.
DiffPhase: Generative Diffusion-based STFT Phase Retrieval
Diffusion probabilistic models have been recently used in a variety of tasks, including speech enhancement and synthesis.
Analysing Diffusion-based Generative Approaches versus Discriminative Approaches for Speech Restoration
In this paper, we systematically compare the performance of generative diffusion models and discriminative approaches on different speech restoration tasks.
Speech Enhancement and Dereverberation with Diffusion-based Generative Models
This matches our forward process which moves from clean speech to noisy speech by including a drift term.
Ranked #19 on
Speech Enhancement
on VoiceBank + DEMAND
Beyond Griffin-Lim: Improved Iterative Phase Retrieval for Speech
Phase retrieval is a problem encountered not only in speech and audio processing, but in many other fields such as optics.
Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain
Score-based generative models (SGMs) have recently shown impressive results for difficult generative tasks such as the unconditional and conditional generation of natural images and audio signals.
Deep Iterative Phase Retrieval for Ptychography
One of the most prominent challenges in the field of diffractive imaging is the phase retrieval (PR) problem: In order to reconstruct an object from its diffraction pattern, the inverse Fourier transform must be computed.
CMInject: Python framework for the numerical simulation of nanoparticle injection pipelines
CMInject simulates nanoparticle injection experiments of particles with diameters in the micrometer to nanometer-regime, e. g., for single-particle-imaging experiments.
Computational Physics Fluid Dynamics Instrumentation and Detectors
