Variable Frame Length Of A Higher Order Speech AR Estimation In A Speech Enhancement System

Abstract

We study some speech enhancement algorithms based on the iterative Wiener filtering method due to Lim-Oppenheim [2], where the AR spectral estimation of the speech is carried out using a 2nd-order analysis. But in our algorithms we consider an AR estimation by means of cumulant analysis. This work extends some preceding papers due to the authors, providing a different frame length where AR estimation is done. Information of previous speech frames is used to initiate speech AR modelling of the current frame. Two parameters are introduced to dessign Wiener filter at first iteration of this iterative algorithm. These parameters are the Interframe Factor IF and the Previous Frame Iteration PFI. They allow a very important noise suppression after processing only fxst iteration of this algorithm, without any appreciable increase of distortion.