基于压缩感知的自适应谱减法语音增强算法
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摘要
针对在压缩感知框架下,噪声的影响会被扩大这个问题,提出了一种新的基于压缩感知的语音增强算法。该方案利用压缩感知下的行阶梯观测矩阵能够保留大部分语音特性的特点,对观测序列进行谱减法消噪,再对得到的观测序列进行基于输入信噪比的自适应重构,最后通过低通滤波器对重构语音进行平滑滤波,除去高频成分。实验结果表明:提出的语音增强方法具有较强的抗噪能力,重构速度快,输出的信噪比高,鲁棒性能好。
A novel speech enhancement algorithm based on compressed sensing is proposed for solving the problem that noise will be expanded under CS framework. Since row echelon measurement matrix can retain a large part of speech characteristics,the traditional spectral subtraction can be used to denoise the measurement sequence under the framework of compressed sensing. The reconstruction algorithm is modified for different input signal-to-noise ratios( SNRs). Finally,a low-pass filter is added to remove high frequency components. Simulation results indicate that the proposed algorithm has a high speech enhancement capability and can speed up the reconstruction. Also,it performs high robustness under different noise intensities.
A novel speech enhancement algorithm based on compressed sensing is proposed for solving the problem that noise will be expanded under CS framework. Since row echelon measurement matrix can retain a large part of speech characteristics,the traditional spectral subtraction can be used to denoise the measurement sequence under the framework of compressed sensing. The reconstruction algorithm is modified for different input signal-to-noise ratios( SNRs). Finally,a low-pass filter is added to remove high frequency components. Simulation results indicate that the proposed algorithm has a high speech enhancement capability and can speed up the reconstruction. Also,it performs high robustness under different noise intensities.
引文
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[11]叶蕾,杨震,郭海燕.基于小波变换和压缩感知的低速率语音编码方案[J].仪器仪表学报,2010,31(7):1569-1575.YE Lei,YANG Zhen,GUO Haiyan.Low bit rate speech coding based on wavelet transform and compressed Sensing[J].Chinese Journal of Scientific Instrument,2010,31(7):1569-1575.(in Chinese)
[12]DONOHO D L.For most large underdetermined systems of linear equations,the minimal L1 norm solution is also the sparsest solution[J].Communications on Pure and Applied Mathematics,2006,59(6):797-829.
[13]石光明,刘丹华,高大化,等.压缩感知理论及其研究进展[J].电子学报,2009,37(5):1070-1081.SHI Guangming,LIU Danhua,GAO Dahua,et al.Advances in theory and application of compressed sensing[J].Acta Electronica Sinica,2009,37(5):1070-1081.(in Chinese)
[14]TROPP J A,GILBERT A C.Signal recovery from random measurements via orthogonal matching pursuit[J].IEEE Transactions on Information Theory,2007,53(12):4655-4666.
[15]杨海蓉,张成,丁大为,等.压缩传感理论与重构算法[J].电子学报,2011,39(1):142-148.YANG Hairong,ZHANG Cheng,DING Dawei,et al.The theory of compressed sensing and reconstruction algorithm[J].Acta Electronica Sinica,2011,39(1):142-148.(in Chinese)
[2]CANDES E J,ROMBERG J,TAO T.Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theory,2006,52(2):489-509.
[3]TSAIG Y,DONOHO D.Extensions of compressed sensing[J].Signal Processing,2006,86(3):533-548.
[4]BOLL S F.Suppression of acoustic noise in speech using spectral subtraction[J].IEEE Transactions on Acoustics,Speech,and Signal Processing,1979,27(2):113-120.
[5]BEROUTI M,SCHWARTZ R,MAKHOUL J.Enhancement of speech corrupted by acoustic noise[C]∥IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP).1979:208-211.
[6]HU Y,LOIZOU P C.A generalized subspace approach for enhancing speech corrupted by colored noise[J].IEEE Transactions on Speech and Audio Processing,2003,11(4):334-341.
[7]GOLDSTEIN J S,REED I S,SCHARF L L.A multistage representation of the Wiener filter based on orthogonal projections[J].IEEE Transactions on Information Theory,1998,44(7):2943-2959.
[8]孙林慧,杨震.基于自适应基追踪去噪的含噪语音压缩感知[J].南京邮电大学学报:自然科学版,2011,31(5):1-6.SUN Linhui,YANG Zhen.Compressed sensing of noisy speech signal based on adaptive basis pursuit de-noising[J].Journal of Nanjing University of Posts and Telecommunications:Natural Science Edition,2011,31(5):1-6.(in Chinese)
[9]叶蕾,杨震.基于压缩感知的语音压缩与重构[J].南京邮电大学学报:自然科学版,2010,30(4):57-60.YE Lei,YANG Zhen.Compression and reconstruction of speech signal based on compressed sensing[J].Journal of Nanjing University of Posts and Telecommunications:Natural Science Edition,2010,30(4):57-60.(in Chinese)
[10]叶蕾,杨震,王天荆,等.行阶梯观测矩阵、对偶仿射尺度内点重构算法下的语音压缩感知[J].电子学报,2012,40(3):429-434.YE Lei,YANG Zhen,WANG Tianjing,et al.Compressed sensing of speech signal based on row echelon measure-ment matrix and dual affine scaling interior point reconstruction method[J].Chinese Journal of Electronics,2012,40(3):429-434.(in Chinese)
[11]叶蕾,杨震,郭海燕.基于小波变换和压缩感知的低速率语音编码方案[J].仪器仪表学报,2010,31(7):1569-1575.YE Lei,YANG Zhen,GUO Haiyan.Low bit rate speech coding based on wavelet transform and compressed Sensing[J].Chinese Journal of Scientific Instrument,2010,31(7):1569-1575.(in Chinese)
[12]DONOHO D L.For most large underdetermined systems of linear equations,the minimal L1 norm solution is also the sparsest solution[J].Communications on Pure and Applied Mathematics,2006,59(6):797-829.
[13]石光明,刘丹华,高大化,等.压缩感知理论及其研究进展[J].电子学报,2009,37(5):1070-1081.SHI Guangming,LIU Danhua,GAO Dahua,et al.Advances in theory and application of compressed sensing[J].Acta Electronica Sinica,2009,37(5):1070-1081.(in Chinese)
[14]TROPP J A,GILBERT A C.Signal recovery from random measurements via orthogonal matching pursuit[J].IEEE Transactions on Information Theory,2007,53(12):4655-4666.
[15]杨海蓉,张成,丁大为,等.压缩传感理论与重构算法[J].电子学报,2011,39(1):142-148.YANG Hairong,ZHANG Cheng,DING Dawei,et al.The theory of compressed sensing and reconstruction algorithm[J].Acta Electronica Sinica,2011,39(1):142-148.(in Chinese)