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• W2434171491 abstract "In this paper, we present a novel single channel speech enhancement method based on joint Deep Neural Network (DNN) and Wiener Filter as a whole network named Wiener Deep Neural Network (WDNN). The proposed method contains two stages: the training stage and the enhancement stage. In the training stage, WDNN predicts the clean speech magnitude spectra and the noise magnitude spectra from noisy speech features simultaneously. Then, the Wiener filter is placed on top of the two output of the neural network as an extra layer to generate the enhanced speech magnitude spectra. Finally, we use the phase of noisy speech to reconstruct clean speech. In the enhancement stage, the well-trained WDNN is fed with the features of noisy speech in order to obtain the enhanced speech. Extensive experimental results show that the proposed method outperforms state-of-the-art methods such as the non-negative matrix factorization (NMF) and the tradition DNN methods." @default.
• W2434171491 created "2016-06-24" @default.
• W2434171491 creator A5011261173 @default.
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• W2434171491 date "2015-12-01" @default.
• W2434171491 modified "2023-09-26" @default.
• W2434171491 title "A novel single channel speech enhancement based on joint Deep Neural Network and Wiener Filter" @default.
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• W2434171491 doi "https://doi.org/10.1109/pic.2015.7489830" @default.
• W2434171491 hasPublicationYear "2015" @default.
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