Over the decades, Bayesian statistical inference has become a staple technique for
modelling human multisensory perception. Many studies have successfully shown how …

This paper presents a novel machine-hearing system that exploits deep neural networks
(DNNs) and head movements for robust binaural localization of multiple sources in …

In this paper, we investigate the tasks of binaural source distance estimation (SDE) and
direction-of-arrival estimation (DOAE) using motion-based cues in a scenario with a walking …

In many daily life communication situations, several sound sources are simultaneously
active. While normal-hearing listeners can easily distinguish the target sound source from …

Despite there being a clear evidence for top-down (eg, attentional) effects in biological
spatial hearing, relatively few machine hearing systems exploit the top-down model-based …

This paper presents a novel machine-hearing system that exploits deep neural networks
(DNNs) and head movements for binaural localisation of multiple speakers in reverberant …

Autonomous systems (ASs) operating in real-world environments are exposed to a plurality
and diversity of sounds that carry a wealth of information for perception in cognitive dynamic …

This paper is concerned with machine localisation of multiple active speech sources in
reverberant environments using two (binaural) microphones. Such conditions typically …

This work studies learning-based binaural sound source localization, under the influence of
head rotation in rever-berant conditions. Emphasis is on whether knowledge of head …

One of the greatest challenges in the development of binaural machine audition systems is
the disambiguation between front and back audio sources, particularly in complex spatial …