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 …

The topic of spherical microphone array signal processing has been gaining importance
since the publications of Meyer and Elko around 2002, and fuelled by many others since …

Localizing audio sources is challenging in real reverberant environments, especially when
several sources are active. We propose to use a neural network built from stacked …

Direction of arrival (DOA) estimation is a fundamental problem in acoustic signal processing.
It is used in a diverse range of applications, including spatial filtering, speech …

Multi-channel signals captured by spatially separated sensors often contain a high level of
data redundancy. A compact signal representation enables more efficient storage and …

A spherical antenna array (SAA) is an array-designed arrangement capable of scanning in
almost all the radiation sphere with constant directivity. It finds recent applications in …

The problem of direction of arrival (DOA) estimation with a circular microphone array has
been addressed with classical source localization methods, such as the model-based …

We present a source localization system for first-order Ambisonics (FOA) contents based on
a stacked convolutional and recurrent neural network (CRNN). We propose to use as input …

A vector-sensor consisting of a monopole sensor collocated with orthogonally oriented
dipole sensors is used for direction of arrival (DOA) estimation in the presence of an …

We propose a direction-of-arrival (DOA) estimation method for Sound Event Localization
and Detection (SELD). Direct estimation of DOA using a deep neural network (DNN), ie …