The recent surge in the use of Deep Neural Networks (DNNs) has also made its mark in the
field of Audio Enhancement (AE), providing much better quality than the classical methods …

Dynamic range limitations in signal processing often lead to clip**, or saturation, in
signals. The task of audio declip** is estimating the original audio signal, given its clipped …

Long (> 200 ms) audio inpainting, to recover a long missing part in an audio segment, could
be widely applied to audio editing tasks and transmission loss recovery. It is a very …

In this article, we deal with the problem of sparsity-based audio inpainting, ie filling in the
missing segments of audio. A consequence of the approaches based on mathematical …

The objective of audio inpainting is to fill a gap in an audio signal. This is ideally done by
reconstructing the original signal or, at least, by inferring a meaningful surrogate signal. We …

Audio inpainting, ie, the task of restoring missing or occluded audio signal samples, usually
relies on sparse representations or autoregressive modeling. In this paper, we propose to …

Audio inpainting plays an important role in addressing incomplete, damaged, or missing
audio signals, contributing to improved quality of service and overall user experience in …

Laser speech measurement is a new sound capture technology based on Laser Doppler
Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote …

This article presents a method for restoring audio signals corrupted by impulsive noise such
as clicks, bursts or scratches. The algorithm takes as input a degraded audio signal and …

We propose a novel audio signal reconstruction model that makes use of a non-linear
estimation algorithm called Cartesian Genetic Programming evolved Artificial Neural …