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Computational Intelligence and Neuroscience
Volume 2017, Article ID 4694860, 14 pages
https://doi.org/10.1155/2017/4694860
Research Article

Deep Recurrent Neural Network-Based Autoencoders for Acoustic Novelty Detection

1Machine Intelligence & Signal Processing Group, Technische Universität München, Munich, Germany
2audEERING GmbH, Gilching, Germany
3Chair of Complex & Intelligent Systems, University of Passau, Passau, Germany
4A3LAB, Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
5Department of Computing, Imperial College London, London, UK

Correspondence should be addressed to Erik Marchi; ed.mut@ihcram.kire

Received 12 July 2016; Accepted 25 September 2016; Published 15 January 2017

Academic Editor: Stefan Haufe

Copyright © 2017 Erik Marchi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [13 citations]

The following is the list of published articles that have cited the current article.

  • Ellen Rushe, and Brian Mac Namee, “Anomaly Detection in Raw Audio Using Deep Autoregressive Networks,” ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3597–3601, . View at Publisher · View at Google Scholar
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