Sorry, you need to enable JavaScript to visit this website.

ICASSP - Sequential MCMC methods for audio signal enhancement

Citation Author(s):
Ruben Claveria, Simon Godsill
Submitted by:
Ruben Claveria
Last updated:
16 May 2022 - 6:45am
Document Type:
Poster
Document Year:
2022
Event:
Presenters:
Ruben Claveria
Paper Code:
AUD-28.6

Abstract

With the aim of addressing audio signal restoration as a sequential inference problem, we build upon Gabor regression to propose a state-space model for audio time series. Exploiting the structure of our model, we devise a sequential Markov chain Monte Carlo algorithm to explore the sequence of filtering distributions of the synthesis coefficients. The algorithm is then tested on a series of denoising examples. Results suggest that the sequential approach is competitive with batch strategies in terms of perceptual quality and signal-to-noise ratio, while showing potential for real-time applications.

up
0 users have voted:

Comments

Presented on May 12 2022