  This article is a survey on deep learning methods for single and multiple
sound source localization. We are particularly interested in sound source
localization in indoor/domestic environment, where reverberation and diffuse
noise are present. We provide an exhaustive topography of the neural-based
localization literature in this context, organized according to several
aspects: 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. This way, an
interested reader can easily comprehend the vast panorama of the deep
learning-based sound source localization methods. Tables summarizing the
literature survey are provided at the end of the paper for a quick search of
methods with a given set of target characteristics.
