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首页> 外文期刊>International Journal of Engineering Research and Applications >A Robust Speech Enhancement By Using Adaptive Kalman Filtering Algorithm
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A Robust Speech Enhancement By Using Adaptive Kalman Filtering Algorithm

机译:自适应卡尔曼滤波算法增强语音的鲁棒性

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Speech enhancement aims to improve speech quality by using various algorithms. The objective of enhancement is improvement in intelligibility and/or overall perceptual quality of degraded speech signal using audio signal processing techniques. Enhancing of speech degraded by noise, or noise reduction, is the most important field of speech enhancement. In this paper a Robust speech enhancement method for noisy speech signals presented in speech signals, which is based on improved Kalman filtering. By using Kalman filtering arise some drawbacks to overcome to modified the conventional Kalman filter algorithm. conventional Kalman filter algorithm needs to calculate the parameters of AR(auto=regressive model),and perform a lot of matrix operations, which is generally called as non- adaptive .In this paper we eliminate the matrix operations and reduces the co mputational complexity and we design a coefficient factor for adaptive filtering, to automatically a mend the estimation of environmental noise by the observation data. Experimental results shows that the Proposed technique effective for speech enhancement compare to conventional Kalman filter
机译:语音增强旨在通过使用各种算法来提高语音质量。增强的目的是使用音频信号处理技术来改善退化语音信号的清晰度和/或整体感知质量。被噪声降低或降低噪声导致的语音增强是语音增强的最重要领域。本文提出了一种基于改进的卡尔曼滤波的鲁棒语音增强方法。通过使用卡尔曼滤波,出现了一些缺点,需要克服,以改进传统的卡尔曼滤波算法。传统的卡尔曼滤波算法需要计算AR(自回归模型)的参数,并执行许多矩阵运算,通常称为非自适应。本文消除了矩阵运算,降低了计算复杂度,我们设计了用于自适应滤波的系数因子,以通过观测数据自动修正环境噪声的估计。实验结果表明,与传统的卡尔曼滤波器相比,所提出的有效的语音增强技术。

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