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Masked Conditional Neural Networks for Audio Classification · arXivDesk

1803.02421Mar 6, 2018Restricted BoltzmannMachine, RBM, Conditional Restricted Boltzmann Machine, CRBM, Music Information Retrieval, MIR, Conditional Neural Network, CLNN, Masked Conditional Neural Network, MCLNN, Deep Neural Network

Masked Conditional Neural Networks for Audio Classification

Fady Medhat, David Chesmore, John Robinson

Machine Learning Machine Learning Sound Audio and Speech Processing

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Abstract

We present the ConditionaL Neural Network (CLNN) and the Masked ConditionaL Neural Network (MCLNN) designed for temporal signal recognition. The CLNN takes into consideration the temporal nature of the sound signal and the MCLNN extends upon the CLNN through a binary mask to preserve the spatial locality of the features and allows an automated exploration of the features combination analogous to hand-crafting the most relevant features for the recognition task. MCLNN has achieved competitive recognition accuracies on the GTZAN and the ISMIR2004 music datasets that surpass several state-of-the-art neural network based architectures and hand-crafted methods applied on both datasets.

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The paper addresses: Masked Conditional Neural Networks for Audio Classification.
We present the ConditionaL Neural Network (CLNN) and the Masked ConditionaL Neural Network (MCLNN) designed for temporal signal recognition.

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Author comment: Restricted BoltzmannMachine, RBM, Conditional Restricted Boltzmann Machine, CRBM, Music Information Retrieval, MIR, Conditional Neural Network, CLNN, Masked Conditional Neural Network, MCLNN, Deep Neural Network