卷积混迭语音信号的联合块对角化盲分离方法  

Blind convolutive separation algorithm for speech signals via joint block diagonalization

作　　者：张华[1] 冯大政[1] 庞继勇[2] 

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,西安710071 [2]西安电子科技大学ISN国家重点实验室,西安710071

出　　处：《声学学报》2009年第2期167-174,共8页Acta Acustica

基　　金：国家自然科学基金(60672128;60702057);国家863计划课题(2007AA01Z288)。

摘　　要：针对语音信号的卷积混迭模型,利用不同语音信号之间的近似独立和短时平稳特性,提出一种基于信号二阶统计量的联合块对角化方法,解决超定卷积盲分离问题。该方法采用非对角线上各子矩阵F-范数的平方和作为联合块对角化性能的评判准则,将原四次代价函数转化为一组较为简单的二次子代价函数,每一子代价函数用于估计酉混迭矩阵的一个子矩阵。依次最小化各子函数,迭代搜索代价函数最小点,得到混迭矩阵的估计。理论分析及实验结果表明,所提方法不仅能够达到与类Jacobi经典方法同样好的分离效果,并且具有更低的计算复杂度、更快的收敛速度和对传输信道阶数、迭代初始值不敏感的特点。A blind speech source separation algorithm for the overdetermined convolutive mixture model in time-domain is proposed via joint block-diagonalization based on the mutual-independence property and the short-time stationary of the speech signals. Taking the sum of the F-norms of all off-diagonal sub-matrices as a criterion, a novel joint block- diagonalization algorithm is proposed to estimate the whole mixture matrix through minimizing a sequence of quadratic subfunctions corresponding to mixture submatrices. Both theoretical analysis and simulation results show that the proposed algorithm has much lower complexity and faster convergence speed than the classical Jacobi-like method with no performance loss. In addition, there almost are no obvious impacts of the channel order and initialization values on the convergence speed.

关 键 词：语音信号 块对角化 混迭 分离方法 卷积 代价函数 JACOBI 对角化方法 

分 类 号：TN912.3[电子电信—通信与信息系统]