This study is a survey of sound source localization and detection methods. The study
provides a detailed classification of the methods used in the fields of science mentioned …

Abstract Sound Source Localization (SSL) systems focus on finding the direction of a sound
source. Sound source localization is an essential feature in robots and humanoids …

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 …

Acoustic data provide scientific and engineering insights in fields ranging from biology and
communications to ocean and Earth science. We survey the recent advances and …

In this paper, we propose a convolutional recurrent neural network for joint sound event
localization and detection (SELD) of multiple overlap** sound events in three-dimensional …

Lacking of adaptation to various array imperfections is an open problem for most high-
precision direction-of-arrival (DOA) estimation methods. Machine learning-based methods …

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme
noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Network …

Supervised learning-based methods for source localization, being data driven, can be
adapted to different acoustic conditions via training and have been shown to be robust to …

This paper proposes a deep neural network for estimating the directions of arrival (DOA) of
multiple sound sources. The proposed stacked convolutional and recurrent neural network …

In this letter, a deep learning framework for direction of arrival (DOA) estimation is
developed. We first show that the columns of the array covariance matrix can be formulated …