DocumentCode
1387561
Title
IMM-based estimation for slowly evolving environments
Author
Kim, Nam Soo
Author_Institution
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
Volume
5
Issue
6
fYear
1998
fDate
6/1/1998 12:00:00 AM
Firstpage
146
Lastpage
149
Abstract
We propose a new approach to environmental parameter estimation for robust speech recognition in adverse conditions. The proposed method is based on the interacting multiple model (IMM) technique widely used in the area of multiple target tracking. Through a number of continuous digit recognition experiments, we can find the effectiveness of the IMM-based approach in slowly evolving environment conditions.
Keywords
Gaussian distribution; Kalman filters; filtering theory; parameter estimation; speech recognition; IMM-based estimation; Kalman filtering; adverse conditions; continuous digit recognition experiments; environmental parameter estimation; interacting multiple model; robust speech recognition; slowly evolving environments; Gaussian distribution; Gaussian noise; Parameter estimation; Piecewise linear approximation; Robustness; Speech recognition; State-space methods; Target tracking; Taylor series; Working environment noise;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/97.681432
Filename
681432
Link To Document