Compression and reconstruction of speech signals based on compressed sensing  

作　　者：梁瑞宇 Zhao li Xi Ji Zhang Xuewu 

机构地区：[1]College of Computer and Information, Hohai University, Nanjing 210098, P. R. China [2]School of Information Science and Engineering, Southeast University, Nanjing 210096, P. R. China

出　　处：《High Technology Letters》2013年第1期37-41,共5页高技术通讯（英文版）

基　　金：Supported by the National Natural Science Foundation of China(No.60472058,60975017);the Fundamental Research Funds for the Central Universities(No.2009B32614,2009B32414)

摘　　要：Based on the approximate sparseness of speech in wavelet basis,a compressed sensing theory is applied to compress and reconstruct speech signals.Compared with one-dimensional orthogonal wavelet transform(OWT),two-dimensional OWT combined with Dmeyer and biorthogonal wavelet is firstly proposed to raise running efficiency in speech frame processing,furthermore,the threshold is set to improve the sparseness.Then an adaptive subgradient projection method(ASPM)is adopted for speech reconstruction in compressed sensing.Meanwhile,mechanism which adaptively adjusts inflation parameter in different iterations has been designed for fast convergence.Theoretical analysis and simulation results conclude that this algorithm has fast convergence,and lower reconstruction error,and also exhibits higher robustness in different noise intensities.Based on the approximate sparseness of speech in wavelet basis, a compressed sensing theory is applied to compress and reconstruct speech signals. Compared with one-dimensional orthogonal wavelet transform （OWT）, two-dimensional OWT combined with Dmeyer and biorthogonal wavelet is firstly proposed to raise running efficiency in speech frame processing, furthermore, the threshold is set to improve the sparseness. Then an adaptive subgradient projection method （ASPM） is adopt- ed for speech reconstruction in compressed sensing. Meanwhile, mechanism which adaptively ad- justs inflation parameter in different iterations has been designed for fast convergence. Theoretical analysis and simulation results conclude that this algorithm has fast convergence, and lower reconstruction error, and also exhibits higher robustness in different noise intensities.

关 键 词：compressed sensing （ CS） orthogonal wavelet transform （ OWT） sparse representation RECONSTRUCTION 

分 类 号：TN912.3[电子电信—通信与信息系统]