Robust Noise Suppression Algorithm with the Kalman Filter Theory for White and Colored Disturbance
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2008-03-01
著者
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TSUJII Shigeo
Research and Development Initiative, Chuo University
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Tsujii S
Institute Of Information Security
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Tsujii Shigeo
Graduate School Of Information Security Institute Of Information Security:research And Development I
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Tsujii Shigeo
Institute Of Information Security
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Tanabe Nari
Department Of Electronic Systems Engineering Tokyo University Of Science
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Tsujii Shigeo
Graduate School Of Information Security Institute Of Information Security
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Tsujii S
Graduate School Of Information Security Institute Of Information Security:research And Development I
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FURUKAWA Toshihiro
Department of Management Science, Tokyo University of Science
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Furukawa Toshihiro
Department Of Management Science Tokyo University Of Science
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