A survey of sound source localization with deep learning methods

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 reverberation and diffuse noise are present. We provide an extensive topography of the neural network-based sound source localization literature in this context, organized according to the neural network architecture, the type of input features, the output strategy (classification or regression), the types of data used for model training and evaluation, and the model training strategy. Tables summarizing the literature survey are provided at the end of the paper, allowing a quick search of methods with a given set of target characteristics. (C) 2022 Acoustical Society of America

Automated summary

This article presents a survey of deep learning methods for single and multiple sound source localization, specifically focusing on indoor environments with reverberation and diffuse noise. The article provides an extensive overview of the literature on neural network-based sound source localization, organized by neural network architecture, input features, output strategy, data types, and model training strategy. Tables summarizing the literature survey are provided for quick reference.