paper-with-me

Recurrent Neural Networks with Stochastic Layers for Acoustic Novelty Detection

2019-02-13 · Duong Nguyen, Oliver S. Kirsebom, Fábio Frazão, Ronan Fablet 외

In this paper, we adapt Recurrent Neural Networks with Stochastic Layers, which are the state-of-the-art for generating text, music and speech, to the problem of acoustic novelty detection. By integrating uncertainty int…

Acoustic Novelty Detection Feature Engineering Novelty Detection

Non-linear prediction with LSTM recurrent neural networks for acoustic novelty detection

2015-10-01 · 2015 International Joint Conference on Neural Networks (IJCNN) 2015 10 · Erik Marchi ; Fabio Vesperini ; Felix Weninger ; Florian Eyben ; Stefano Squartini ; Björn Schuller

Acoustic novelty detection aims at identifying abnormal/novel acoustic signals which differ from the reference/normal data that the system was trained with. In this paper we present a novel approach based on non-linear p…

Acoustic Novelty Detection Denoising Novelty Detection

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

2015-08-06 · 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015 8 · Erik Marchi ; Fabio Vesperini ; Florian Eyben ; Stefano Squartini ; Björn Schuller

Acoustic novelty detection aims at identifying abnormal/novel acoustic signals which differ from the reference/normal data that the system was trained with. In this paper we present a novel unsupervised approach based on…

Acoustic Novelty Detection Denoising Novelty Detection

Papers Acoustic Novelty Detection

Recurrent Neural Networks with Stochastic Layers for Acoustic Novelty Detection

Non-linear prediction with LSTM recurrent neural networks for acoustic novelty detection

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