Deep neural networks for audio scene recognition

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...

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Bibliographic Details
Main Authors: Petetin, Yohan, Laroche, Cyrille, Mayoue, Aurelien
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
audio scene recognition
Context
deep belief networks
Deep neural networks
Europe
Mel frequency cepstral coefficient
Signal processing
Training
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Summary: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.
ISSN:2076-1465
DOI:10.1109/EUSIPCO.2015.7362358