Noise Power Spectrum Estimation for Speech Enhancement Using an Autoregressive Model for Speech Power Spectrum Dynamics

In this paper we propose a method for estimating the non-stationary noise power spectral density (PSD) given a noisy speech signal. The method is based on an autoregressive (AR) model of the speech PSD dynamics combined with a Kalman filtering based noise PSD estimation technique. Objective and subjective performance evaluations show that the speech enhancement scheme utilizing the proposed noise PSD estimation technique achieves significant improvements over a system using a stationary noise estimate as well as compared to a system that uses a noise tracker developed in our previous work