Multichannel Audio Source Separation With Deep Neural Networks.

IEEE/ACM Transactions on Audio, Speech, and Language Processing(2016)

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摘要
This article addresses the problem of multichannel audio source separation. We propose a framework where deep neural networks (DNNs) are used to model the source spectra and combined with the classical multichannel Gaussian model to exploit the spatial information. The parameters are estimated in an iterative expectation-maximization (EM) fashion and used to derive a multichannel Wiener filter. We...
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关键词
Source separation,Cost function,Spectrogram,Covariance matrices,Speech enhancement,Training,Iterative algorithms
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