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 …

While neural networks have acted as a strong unifying force in the design of modern AI
systems, the neural network architectures themselves remain highly heterogeneous due to …

This paper presents a novel approach for indoor acoustic source localization using
microphone arrays, based on a Convolutional Neural Network (CNN). In the proposed …

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 …

The reverberation time of an acoustic environment is a useful parameter for applications
including source localisation, speech recognition and mixed reality. However, estimating the …

What happens when artificial sensors are coupled with the human senses? Using
technology to extend the senses is an old human dream, on which sensory substitution and …

Learning from data in the quaternion domain enables us to exploit internal dependencies of
4D signals and treating them as a single entity. One of the models that perfectly suits with …

Recent work on acoustic parameter estimation indicates that geometric room volume can be
useful for modeling the character of an acoustic environment. However, estimating volume …

This paper presents an estimation of the sound source location using deep neural networks
in order to provide auditory perception of a humanoid robot. Estimation of a moving sound …

Deep Learning-based Automatic Speech Recognition (ASR) models are very successful, but
hard to interpret. To gain a better understanding of how Artificial Neural Networks (ANNs) …