Localization, Detection and Tracking of Multiple Moving Sound Sources with a Convolutional Recurrent Neural Network
Year: 2019

This paper investigates the joint localization, detection, and tracking of sound events using a convolutional recurrent neural network (CRNN). We use a CRNN previously proposed for the localization and detection of stationary sources, and show that the recurrent layers enable the spatial tracking of moving sources when trained with dynamic scenes. The tracking performance of the CRNN is compared with a stand-alone tracking method that combines a multisource direction of arrival estimator and a p