通过实现二阶快速自适应卡尔曼滤波算法来提高语音质量

C. Pandey, S. Nemade
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引用次数: 7

摘要

语音信号增强是语音处理、语音识别和说话人识别的重要而主要的过程之一。本文提出了语音信号增强的快速处理方法,即快速自适应卡尔曼滤波的二阶实现。与快速自适应卡尔曼滤波相比,该方法提高了传统二阶自适应卡尔曼滤波的处理时间和输出信噪比。卡尔曼滤波的传统算法采用不同的矩阵运算来进行语音增强。这些矩阵运算增加了处理时间,也降低了卡尔曼滤波器的自适应性能。二阶自适应卡尔曼滤波提高了传统卡尔曼滤波的输出信噪比,但该方法使矩阵运算几乎增加了一倍,并进一步增加了执行时间。本文提出了一种快速自适应二阶卡尔曼滤波器,减少了传统二阶卡尔曼滤波器的处理时间,同时具有有效的输出信噪比。也可以说,该算法提高了一阶快速自适应卡尔曼滤波器的输出信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancement of the speech quality by the implementation of Second Order Fast Adaptive Kalman Filter algorithm
Speech signal enhancement is one of the important and primary processes used in speech processing, speech recognitions and speaker recognitions. This paper proposed the fast processed method for speech signal enhancement, which is the second order implementation of the fast adaptive Kalman filtering. This proposed method improves the processing time of conventional second order adaptive Kalman filter as well as output SNR as compared to the fast adaptive Kalman filter. The Kalman filter's conventional algorithm uses defferent matrix operations to perform speech enhancement. These matrix operations increases the processing time and reduces the adaptability property of Kalman filter as well. Second order Adaptive Kalman Filter improves output SNR of conventional Kalman Filter, but this method almost doubles the matrix operation and further increases the performance time. This paper proposes the Fast Adaptive Second Order Kalman Filter, which reduced processing time of conventional second order Kalman Filter with effective output SNR. We can also say that this proposed algorithm improves the output SNR of First Ordered Fast Adaptive Kalman Filter.
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