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arXiv 1803.024212019-03-23stat.MLcs.LGcs.SDeess.AS

Masked Conditional Neural Networks for Audio Classification

Department of Electronic Engineering University of York（约克大学电子工程系）；University of York（约克大学）

Fady Medhat, David Chesmore, John Robinson

备注：: Restricted BoltzmannMachine, RBM, Conditional Restricted Boltzmann Machine, CRBM, Music Information Retrieval, MIR, Conditional Neural Network, CLNN, Masked Conditional Neural Network, MCLNN, Deep Neural Network
发表信息：: International Conference on Artificial Neural Networks (ICANN) Year: 2017
DOI：: 10.1007/978-3-319-68612-7_40

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英文摘要：

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.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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