A SECOND-ORDER FEATURE WINDOW METHOD FOR BLIND SEPARATION OF SPEECH SIGNALS CORRUPTED BY COLOR NOISE

摘要：

A second-order feature window (SOFW) method is proposed for blind separation of speech signals corrupted by color background noise based on the short-time stationarity property of speech signals.At first the new prewhitening algorithm is developed to remove the effect of color noise, then the prewhitened data is partitioned continually by feature window with the length equal to the cycle of the fundamental tone of speech signals, after that the speech signal can be separated blindly by estimating the Givens rotation parameters based on the joint approximately diagonalization theory.This novel second order statistics-based method exploits the temporal structure inherent in speech signals, it is simple and can be used as the preprocessing stage for speech recognition systems.Simulation results show that it outperforms the existing typical blind source separation algorithm for speech signals contaminated by color noise.

关键词： Blind separation Speech signals Color noise Second-order feature window method

作者: YU-LIN LIU SHUN XU MING-QI LI

作者单位: DSP Lab, Chongqing Communication College, Chongqing 400035, P.R.China Schoool of Applied Mathematics, UESTC, Chengdu 610054, P.R.China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 3454-3458

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）