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

Author

Batina, Ivo ; Jensen, Jesper ; Heusdens, Richard

Author_Institution

Inf. & Commun. Theory Group, Delft Univ. of Technol.

Volume

3

fYear

2006

fDate

14-19 May 2006

Abstract

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

Keywords

Kalman filters; autoregressive processes; filtering theory; speech enhancement; Kalman filtering; autoregressive model; noise power spectrum estimation; noisy speech signal; speech enhancement; speech power spectrum dynamics; Additive noise; Filtering; Frequency estimation; Kalman filters; Signal to noise ratio; Spectral analysis; Speech enhancement; Speech processing; Statistics; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1660841

Filename

1660841