Speech Enhancement Employing Modified a Priori SNR Estimation

S. Ou, Xiaohui Zhao, Ying Gao
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引用次数: 11

Abstract

In order to improve the performance of a speech enhancement system, Plapous introduced a novel method called two-step noise reduction (TSNR) technique to refine the a priori SNR estimation of the decision-directed (DD) approach. However, the performance of this method depends on the choice of gain function. In this paper, we propose a modified approach for the a priori SNR estimation in DCT domain with two steps like the TSNR method. While in the second step, the proposed approach computes directly the square of clean speech component using the estimated a priori SNR of the DD approach, its result is not restricted on the gain function, and thus the drawback of the TSNR method is removed while the advantages are kept. A number of objective tests under various conditions are provided, and the results show the improved performance of our approach.
基于改进先验信噪比估计的语音增强
为了提高语音增强系统的性能,Plapous引入了一种称为两步降噪(TSNR)的新方法来改进决策导向(DD)方法的先验信噪比估计。然而,该方法的性能取决于增益函数的选择。本文提出了一种改进的DCT域先验信噪比估计方法,该方法与TSNR方法类似,分两步进行。在第二步中,该方法利用DD方法估计的先验信噪比直接计算干净语音分量的平方,其结果不受增益函数的限制,从而在保留TSNR方法优点的同时消除了TSNR方法的缺点。在各种条件下进行了大量的客观测试,结果表明我们的方法提高了性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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