NDLI: A Kalman Filter based Fast Noise Suppression Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Tanabe, N. Furukawa, T. Tsujii, S.
Copyright Year	2009
Description	Author affiliation: Tokyo University of Science, Suwa, 5000-1 Toyohira, Chino, Nagano, 391-0292, Japan, nari@rs.suwa.tus.ac.jp (Tanabe, N.) \|\| Institute of information Security, 2-14-1 Tsuruya-cho, Kanagawa-ku, Yokohama 221-0835, Japan, tsujii@iisec.ac.jp (Tsujii, S.) \|\| Tokyo University of Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-0825, Japan, furukawa@ms.kagu.tus. ac.jp (Furukawa, T.)
Abstract	We have proposed a robust noise suppression algorithm with Kalman filter theory [7]. In this paper, we propose a fast noise suppression algorithm by modifying the canonical state space model in [7]. The algorithm aims to achieve robust noise suppression with reduced computational complexity without sacrificing high quality of speech signal. The remarkable features of the proposed algorithm are that it can be realized by 3 multiplications and that it has the same performances or better ones compared with [7] despite the reduction of computational complexity under the same environments, using only the Kalman filter algorithm for the proposed canonical state space model with the colored driving source: (i) a vector state equation is composed of the only speech signal, and (ii) a scalar observation equation is composed of speech signal and additive noise. We have confirmation of validity of the proposed canonical state space model with the colored driving source, and also show the effectiveness through numerical results and subjective evaluation results.
Starting Page	5
Ending Page	9
File Size	1595164
Page Count	5
File Format	PDF
ISBN	9781424436774
DOI	10.1109/DSP.2009.4785886
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-01-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech enhancement State-space methods Additive noise Computational complexity Equations Noise robustness Noise reduction Signal generators Noise generators Information security
Content Type	Text
Resource Type	Article

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