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机构地区:[1]Institute of Communications Engineering, PLA Univ. of Sci. & Tech., Nanjing 210007, China
出 处:《Journal of Electronics(China)》2007年第3期332-337,共6页电子科学学刊(英文版)
基 金:the Natural Science Foundation of Jiangsu Province (No.BK2006001).
摘 要:In this paper,two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) es-timator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then,MMSE estimators under speech presence uncertainty are derived. Furthermore,the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new deci-sion-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years.In this paper, two speech enhancement systems with supergaussian speech modeling are presented. The clean speech components are estimated by Minimum-Mean-Square-Error (MMSE) estimator under the assumption that the DCT coefficients of clean speech are modeled by a Laplacian or a Gamma distribution and the DCT coefficients of the noise are Gaussian distributed. Then, MMSE estimators under speech presence uncertainty are derived. Furthermore, the proper estimators of the speech statistical parameters are proposed. The speech Laplacian factor is estimated by a new decision-directed method. The simulation results show that the proposed algorithm yields less residual noise and better speech quality than the Gaussian based speech enhancement algorithms proposed in recent years.
关 键 词:Speech enhancement Speech model Minimum-Mean-Square-Error (MMSE) Super Ganssian
分 类 号:TN912[电子电信—通信与信息系统]
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