A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 2015-August, Issue , 2015, Pages 1996-2000

  Marchi, Erik ^a   Vesperini, Fabio ^b   Eyben, Florian ^a   Squartini, Stefano ^b   Schuller, Bjorn ^a,c,d  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITÀ POLITECNICA DELLE MARCHE   (Italy)

^c UNIVERSITY OF PASSAU   (Germany)

^d IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Acoustic Novelty Detection; Bidirectional LSTM; Denoising Autoencorder; Recurrent Neural Networks

Indexed keywords

AUDIO SIGNAL PROCESSING; LEARNING SYSTEMS; RECURRENT NEURAL NETWORKS; SPEECH COMMUNICATION;

ACOUSTIC SIGNALS; BIDIRECTIONAL LSTM; DE-NOISING; DENOISING AUTOENCODER; NOVELTY DETECTION; RECONSTRUCTION ERROR; SPECTRAL FEATURE; UNSUPERVISED APPROACHES;

LONG SHORT-TERM MEMORY;

EID: 84946055465     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2015.7178320     Document Type: Conference Paper

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