1 research outputs found
Integrated Speech Enhancement Method Based on Weighted Prediction Error and DNN for Dereverberation and Denoising
Both reverberation and additive noises degrade the speech quality and
intelligibility. Weighted prediction error (WPE) method performs well on the
dereverberation but with limitations. First, WPE doesn't consider the influence
of the additive noise which degrades the performance of dereverberation.
Second, it relies on a time-consuming iterative process, and there is no
guarantee or a widely accepted criterion on its convergence. In this paper, we
integrate deep neural network (DNN) into WPE for dereverberation and denoising.
DNN is used to suppress the background noise to meet the noise-free assumption
of WPE. Meanwhile, DNN is applied to directly predict spectral variance of the
target speech to make the WPE work without iteration. The experimental results
show that the proposed method has a significant improvement in speech quality
and runs fast