This article is a survey of deep learning methods for single and multiple sound source
localization, with a focus on sound source localization in indoor environments, where …

Imagine being in a crowded room with a cacophony of speakers and having the ability to
focus on or remove speech from a specific 2D region. This would require understanding and …

While sound source localization (SSL) using a spherical microphone array system can be
applied to obtain visual beam patterns of source distribution maps in a range of …

Conventional microphone array methods for the characterization of sound sources that
require a focus-grid are, depending on the grid resolution, either computationally …

The use of machine learning for localization of sound sources from microphone array data
has increased rapidly in recent years. Newly developed methods are of great value for …

In this article, we consider gridless source localization based on the spatial covariance
matrix of acoustical data collected by an array of microphones. Covariance matrix fitting …

Beamforming acoustic imaging technology, utilizing phased microphone arrays, enables
precise sound source localization and finds widespread application in aerodynamic wind …

Abstract Deep Neural Network (DNN) models offer an attractive alternative to existing
acoustic source imaging techniques, such as acoustic beamforming, due to their ever …

Deep learning has achieved a vital breakthrough in the sound source localization and has
overcome the limitations of conventional model-based approaches. The deep learning …

In this work, a new grid-free global optimization algorithm that combined the image source
model (ISM) and state transition algorithm (STA) was proposed to realize the sound source …