Deep neural networks for audio scene recognition
Résumé
These last years, artificial neural networks (ANN) have known a renewed interest since efficient training procedures have emerged to learn the so called deep neural networks (DNN), i.e. ANN with at least two hidden layers. In the same time, the computational auditory scene recognition (CASR) problem which consists in estimating the environment around a device from the received audio signal has been investigated. Most of works which deal with the CASR problem have tried to ind well-adapted features for this problem. However, these features are generally combined with a classical classi-ier.
In this paper, we introduce DNN in the CASR ield and we show that such networks can provide promising results and perform better than standard classiiers when the same features are used.
Mots clés
Deep neural network
neural network
deep learnin
audio scene recognition
audio signal processing
belief networks
machine learning
artificial intelligence
neural nets
signal classification
Training
Mel frequency cepstral coefficient
computational auditory scene recognition problem
artificial neural networks
ANN
training procedures
CASR problem
deep belief networks
Index Terms-Deep neural networks
deep beliefs net- works
| Origine | Fichiers produits par l'(les) auteur(s) |
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