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首页> 外文会议>International conference on information technology and industrial engineering >Novel Laplacian Factor Estimation Algorithm for Speech Enhancement
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Novel Laplacian Factor Estimation Algorithm for Speech Enhancement

机译：语音增强的新型拉普拉斯因子估计算法

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摘要

Based on the property of generalized Gaussian distribution model and its shape parameter, a novel approach for Laplacian factor estimation is presented, which indirectly attains the estimation of Laplacian factor using its relation with the variance of clean speech components. As for the estimation for speech components variance, a new algorithm is used by making use of the noisy speech components and clean speech variance in previous frame to compute the current frame's speech variance. By combining the given two approaches, the estimated Laplacian factor can not be affected by noise components energy and the obtained result keeps accurate. Simulation results demonstrate that the proposed algorithm possesses good performance under different kinds of noise.
机译：基于广义高斯分布模型及其形状参数的性质，提出了一种新颖的拉普拉斯因子估计方法，它间接地达到了利用其与清洁语音组分方差关系的拉普拉斯因子的估计。对于语音组件方差的估计，通过利用嘈杂的语音组件和先前帧中的清洁语音方差来使用新算法来计算当前帧的语音方差。通过组合给定的两种方法，估计的拉普拉斯因子不能受到噪声分量能量的影响，并且所获得的结果保持准确。仿真结果表明，所提出的算法在不同类型的噪声下具有良好的性能。

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