Fast converging iterative Kalman filtering for speech enhancement using long and overlapped tapered windows with large side lobe attenuation

Loading...
Thumbnail Image
File version
Author(s)
So, Stephen
Paliwal, Kuldip K
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)

Satoshi Nakamura

Date
2010
Size

653038 bytes

File type(s)

application/pdf

Location

Makuhari, JAPAN

License
Abstract

In this paper, we propose an iterative Kalman filtering scheme that has faster convergence and introduces less residual noise, when compared with the iterative scheme of Gibson, et al. This is achieved via the use of long and overlapped frames as well as using a tapered window with a large side lobe attenuation for linear prediction analysis. We show that the Dolph-Chebychev window with a -200 dB side lobe attenuation tends to enhance the dynamic range of the formant structure of speech corrupted with white noise, reduce prediction error variance bias, as well as provide for some spectral smoothing, while the long overlapped frames provide for reliable autocorrelation estimates and temporal smoothing. Speech enhancement experiments on the NOIZEUS corpus show that the proposed method outperformed conventional iterative and non-iterative Kalman filters as well as other enhancement methods such as MMSE-STSA and PSC.

Journal Title
Conference Title

11TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2010 (INTERSPEECH 2010), VOLS 1-2

Book Title
Edition
Volume
Issue
Thesis Type
Degree Program
School
DOI
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© 2010 ISCA and the Authors. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference's website or contact the authors.

Item Access Status
Note
Access the data
Related item(s)
Subject

Signal processing

Persistent link to this record
Citation