Learning-based methods have become ubiquitous in speaker localization. Existing systems
rely on simulated training sets for the lack of sufficiently large, diverse and annotated real …

Blind acoustic parameter estimation consists in inferring the acoustic properties of an
environment from recordings of unknown sound sources. Recent works in this area have …

Increasing interest in unmanned aerial vehicles (UAVs), commonly referred to as drones,
has occurred in recent years. Search and rescue scenarios where humans in emergency …

This paper presents a new dataset of measured multichannel room impulse responses
(RIRs) named dEchorate. It includes annotations of early echo timings and 3D positions of …

It is commonly observed that acoustic echoes hurt per mance of sound source localization
(SSL) methods. We troduce the concept of microphone array augmentation echoes …

Learning-based methods have become ubiquitous in sound source localization (SSL).
Existing systems rely on simulated training sets for the lack of sufficiently large, diverse and …

In the context of building acoustics and the acoustic diagnosis of an existing room, it
introduces and investigates a new approach to estimate the mean absorption coefficients …

This paper introduces a new framework for supervised sound source localization referred to
as virtually-supervised learning. An acoustic shoe-box room simulator is used to generate a …

Recent deep neural network based methods provide accurate binaural source localization
performance. These data-driven models map measured binaural cues directly to source …

Recent data-driven approaches for binaural source localization are able to learn the non-
linear functions that map measured bin-aural cues to source locations. This is done either by …