Speech enhancement for drone audition is made challenging by the strong ego-noise from
the rotating motors and propellers, which leads to extremely low signal-to-noise ratios (eg …

This paper introduces DREGON, a novel publicly-available dataset that aims at pushing
research in sound source localization using a microphone array embedded in an unmanned …

We propose a time-frequency processing method that localizes and enhances a target
sound by exploiting spectral and spatial characteristics of the ego-noise captured by a …

This article fills the gap between the growing interest in signal processing based on Deep
Neural Networks (DNN) and the new application of enhancing speech captured by …

Acoustic sensing from a multi-rotor drone is heavily degraded by the strong ego-noise
produced by the rotating motors and propellers. To address this problem, we propose a …

In this article, we address the problem of acoustic source localization using a microphone
array mounted on multirotor unmanned aerial vehicles (UAVs). Conventional localization …

Sound source localization from a flying drone is a challenging task due to the strong ego-
noise from rotating motors and propellers as well as the movement of the drone and the …

The rapid development of unmanned aerial vehicle (UAV) market has triggered the demand
for UAV structural health monitoring technology, and blade damage has received extensive …

This paper presents a perception-aware path planner for active SLAM in dynamic
environments using micro-aerial vehicles (MAV). The “Next-Best-View” planner (NBVP …

Underdetermined blind source separation of speech mixtures is a challenging issue in the
classical “Cocktail-party” problem. Recently, there has been attention to use dictionary …