Title
Robust Noise Suppression Algorithm with the Kalman Filter Theory for White and Colored Disturbance
Abstract
We propose a noise suppression algorithm with the Kalman filter theory. The algorithm aims to achieve robust noise suppression for the additive white and colored disturbance from the canonical state space models with (i) a state equation composed of the speech signal and (ii) an observation equation composed of the speech signal and additive noise. The remarkable features of the proposed algorithm are (1) applied to adaptive white and colored noises where the additive colored noise uses babble noise, (2) realization of high performance noise suppression without sacrificing high quality of the speech signal despite simple noise suppression using only the Kalman filter algorithm, while many conventional methods based on the Kalman filter theory usually perform the noise suppression using the parameter estimation algorithm of AR (auto-regressive) system and the Kalman filter algorithm. We show the effectiveness of the proposed method, which utilizes the Kalman filter theory for the proposed canonical state space model with the colored driving source, using numerical results and subjective evaluation results.
Year
DOI
Venue
2008
10.1093/ietfec/e91-a.3.818
IEICE Transactions
Keywords
Field
DocType
noise suppression,kalman filter theory,speech signal,high performance noise suppression,simple noise suppression,colored disturbance,robust noise suppression algorithm,babble noise,additive noise,robust noise suppression,kalman filter algorithm,noise suppression algorithm,state space model,kalman filter,colored noise
Value noise,Extended Kalman filter,Colors of noise,Fast Kalman filter,Control theory,Salt-and-pepper noise,Algorithm,Stochastic resonance,Invariant extended Kalman filter,Gaussian noise,Mathematics
Journal
Volume
Issue
ISSN
E91-A
3
0916-8508
Citations 
PageRank 
References 
4
0.64
5
Authors
3
Name
Order
Citations
PageRank
Nari Tanabe151.95
Toshihiro Furukawa25222.17
Shigeo Tsujii3598131.15