| Single Channel Speech Enhancement by De-noising Using Stationary Wavelet Transform |
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| 引用本文： | ZHANG De-xiang GAO Qing-wei CHEN Jun-ning. Single Channel Speech Enhancement by De-noising Using Stationary Wavelet Transform[J]. 中国电子科技, 2006, 4(1): 39-42 |
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| 作者姓名： | ZHANG De-xiang GAO Qing-wei CHEN Jun-ning |
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| 作者单位： | [1]Key Lab of Intelligent Computing and Signal Processing, Anhui University Hefei 230039 China [2]School of Electronic Science and Technology, Anhui University Hefei 230039 China |
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| 基金项目： | Supported by the Education Foundation of Anhui Province （No.2002kj003） |
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| 摘 要： | It is classical problem to extract signal itself from noise signal in speech processing. We can separate them according to their different statistic characters. Commonly the frequency band of noise is wide but that of original signal is limited and mainly lies in low frequency bands. How to eliminate noise effect becomes a challenging problem in speech processing. Speech enhancement algorithms have been developing considerably, many theories and approaches have been brought forward to suppress…
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| 关 键 词： | 小波变换 语音增强 SNR 信号接收 信噪比 |
| 收稿时间： | 2005-09-19 |
Single Channel Speech Enhancement by De-noising Using Stationary Wavelet Transform |
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| ZHANG De-xiang,GAO Qing-wei,CHEN Jun-ning. Single Channel Speech Enhancement by De-noising Using Stationary Wavelet Transform[J]. Journal of Electronic Science Technology of China, 2006, 4(1): 39-42 |
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| Authors: | ZHANG De-xiang GAO Qing-wei CHEN Jun-ning |
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| Abstract: | A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery signal is reconstructed. The time invariant characteristics of stationary wavelet transform is particularly useful in speech de-noising. Experimental results show that the proposed speech enhancement by de-noising algorithm is possible to achieve an excellent balance between suppresses noise effectively and preserves as many target characteristics of original signal as possible. This de-noising algorithm offers a superior performance to speech signal noise suppress. |
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| Keywords: | stationary wavelet transform speech enhancement de-noising SNR |
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