A Speech Signal Sparse Representation Algorithm Based on Adaptive Overcomplete Dictionary
Wang Tian-jing①② Zheng Bao-yu① Yang Zhen①
①(Key Lab of “Broadband Wireless Communication and Sensor Network Technology”, Ministry of Education, Nanjing University of Posts & Telecommunications, Nanjing 210003, China) ②(School of Science, Nanjing University of Technology, Nanjing 210009, China)
Abstract：The sparse representation based on overcomplete dictionary is a new signal representation theory. Recent activities in this field concentrate mainly on the study of dictionary design algorithm and sparse decomposition algorithm. In this paper, a novel speech signal sparse representation algorithm is proposed based on adaptive overcomplete dictionary. Considering stationary signal with autocorrelation function of exponential decay, an adaptive overcomplete dictionary is constructed in terms of the Karhunen-Loève (K-L) expansion. Furthermore, an effective algorithm based on the nonlinear approximation is proposed to obtain sparse decomposition of signal with the adaptive dictionary. The experimental results indicate that short-term stationary speech signal sparse representation based on the adaptability and algebraic structure of atom in the overcomplete dictionary has higher sparsity and better reconstructive precision. The sparse representation algorithm can preferably be used in compressed sensing.
王天荆, 郑宝玉, 杨震. 基于自适应冗余字典的语音信号稀疏表示算法[J]. 电子与信息学报, 2011, 33(10): 2372-2377.
Wang Tian-Jing, Zheng Bao-Yu, Yang Zhen. A Speech Signal Sparse Representation Algorithm Based on Adaptive Overcomplete Dictionary. , 2011, 33(10): 2372-2377.
2011, Vol. 33 
