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A recurrent neural network for sound-source motion tracking and prediction

Murray, J. C.; Erwin, H.; Wermter, S.

Authors

H. Erwin

S. Wermter

Abstract

Recurrent neural networks (RNN) have been used in many applications for both pattern detection and prediction. This paper shows the use of RNN's as a speed classifier and predictor for a robotic sound source tracking system. The system requires extensive training to classify all possible speeds to enable dynamic tracking of the most prominent sound within the environment.

Start Date Jul 31, 2004
Publication Date Dec 1, 2005
Volume 4
Pages 2232-2236
Series ISSN 2161-4393
Book Title Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.
ISBN 0780390482
Institution Citation Murray, J. C., Erwin, H., & Wermter, S. (2005). A recurrent neural network for sound-source motion tracking and prediction. In Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005, 2232-2236. doi:10.1109/IJCNN.2005.1556248
DOI https://doi.org/10.1109/IJCNN.2005.1556248
Keywords Recurrent neural networks; Tracking; Robot sensing systems; Signal to noise ratio; Azimuth; Microphones; Hybrid intelligent systems; Manufacturing; Human robot interaction; Navigation
Publisher URL https://ieeexplore.ieee.org/document/1556248