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Both reverberation and additive noises degrade the speech quality andintelligibility. Weighted prediction error (WPE) method performs well on thedereverberation but with limitations. First, WPE doesn't consider the influenceof the additive noise which degrades the performance of dereverberation.Second, it relies on a time-consuming iterative process, and there is noguarantee or a widely accepted criterion on its convergence. In this paper, weintegrate deep neural network (DNN) into WPE for dereverberation and denoising.DNN is used to suppress the background noise to meet the noise-free assumptionof WPE. Meanwhile, DNN is applied to directly predict spectral variance of thetarget speech to make the WPE work without iteration. The experimental resultsshow that the proposed method has a significant improvement in speech qualityand runs fast.

Integrated Speech Enhancement Method Based on Weighted Prediction Error and DNN for Dereverberation and Denoising