基于压缩感知的分布式语音压缩与重构  

Distributed Speech Compression and Reconstruction Based on Compressed Sensing Theory

作　　者：孙林慧[1] 杨震[1] 

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003

出　　处：《信号处理》2010年第6期824-829,共6页Journal of Signal Processing

基　　金：国家863课题(2006AA010102);国家自然科学基金(60971129;60902065);南京邮电大学‘青蓝计划’基金资助(NY208038)

摘　　要：本文首先阐述了压缩感知(CS)的理论框架,然后分析了语音信号的特点——短时平稳性、离散余弦(DCT)基下的稀疏性,最后提出了基于CS理论的分布式语音压缩重构的框架。基于此框架采用基追踪(BP)和正交匹配追踪(OMP)算法对已压缩的语音信号进行重构,得出结论:每帧语音信号选取的帧长的大小,基于CS理论压缩得到的观测数的多少,都对重构性能有影响。In this paper,the CS framework is introduced firstly,and then the short-term stability of speech signal and the sparsity in the discrete cosine transform basis of speech signal are analyzed.Secondly,a new distributed speech signal compression and reconstruction framework based on compressed sensing theory is proposed.Via basis pursuit（BP） and orthogonal matching pursuit（OMP）,it is demonstrated that the performance of reconstruction is correlated with the number of measurements and the length of frames.

关 键 词：压缩感知 分布式语音压缩与重构 短时平稳性 稀疏性 基追踪 正交匹配追踪 

分 类 号：TN912.3[电子电信—通信与信息系统]