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含噪语音实时迭代维纳滤波
引用本文:王景芳.含噪语音实时迭代维纳滤波[J].计算机工程与应用,2011,47(19):132-135.
作者姓名:王景芳
作者单位:湖南涉外经济学院电气工程系,长沙,410205
摘    要:针对传统去噪方法在强背景噪声情况下,提取声音信号的能力变弱甚至失效与对不同噪声环境适应性差,提出了迭代维纳滤波声音信号特征提取方法。给出了语音噪声频谱与功率谱信噪比迭代更新机制与具体实施方案。实验仿真表明,该算法能有效地去噪滤波,显著地提高语音识别系统性能,且在不同的噪声环境和信噪比条件下具有鲁棒性。该算法计算代价小,简单易实现,适用于嵌入式语音识别系统。

关 键 词:声信号  迭代维纳滤波  去噪  自适应处理
修稿时间: 

Iterative Wiener filtering-based real-time voice in noises
WANG Jingfang.Iterative Wiener filtering-based real-time voice in noises[J].Computer Engineering and Applications,2011,47(19):132-135.
Authors:WANG Jingfang
Affiliation:WANG Jingfang Department of Electric Engineering,Hunan International Economics University,Changsha 410205,China
Abstract:As many traditional de-noising methods fail in the intensive noises environment and be unadaptable in various noisy environments,a method based on iterative Wiener filtering feature extraction is applied for acoustic signals.It frames the acoustic signals at first.Then,the iterative-renewing methods are advanced in noising spectral frequency and Signal-to-Noise ratio(SNR)of spectral power.This method is implemented in detail.The experimental results show that the proposed algorithm can filter noise from voice effectively and improve the performance of automatic speech recognition system significantly.It is proved to be robust under various noisy environments and SNR conditions.The algorithm is of low computational complexity which is suitable for embedded automatic speech recognition system application.
Keywords:acoustic signal  iterative Wiener filtering  de-noising  adaptive processing
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