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首页> 外文期刊>International journal of speech technology >A new dual subband fast NLMS adaptive filtering algorithm for blind speech quality enhancement and acoustic noise reduction
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A new dual subband fast NLMS adaptive filtering algorithm for blind speech quality enhancement and acoustic noise reduction

机译:一种新的双子带快速NLMS自适应滤波算法,用于盲语音质量增强和声学噪声降低

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This paper discusses the problem of acoustic noise reduction and speech enhancement through the forward blind source separation structure. Recently we have proposed a new combination between the forward blind source separation structure and the fast normalized least mean square algorithm that provides an efficient dual algorithm for noise reduction and speech enhancement applications. In this paper we propose a new subband implementation of this recent dual algorithm, this last allows improving the speed convergence behavior of the previous proposed algorithm in its fullband form. The performance of the proposed dual subband algorithm is compared with its fullband version of the dual fast normalized least mean square algorithm and the classical fullband dual normalized least mean square algorithm, and the two channel subband forward algorithm in terms of several objective criteria. The obtained results show the good performances of the proposed dual sub-band algorithm.
机译:本文讨论了通过前向盲源分离结构来降低声学噪声和增强语音的问题。最近,我们提出了前向盲源分离结构和快速归一化最小均方算法之间的新组合,该组合为降噪和语音增强应用提供了有效的双重算法。在本文中,我们提出了这种最新的双重算法的新子带实现,这最后可以改进先前提出的算法的全频带形式的速度收敛行为。将所提出的双子带算法的性能与双快速归一化最小均方算法的全频带版本,经典全带双归一化最小均方算法以及两个信道子带正向算法进行比较。所得结果表明了所提出的双子带算法的良好性能。

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