On the Effectiveness of the ICA-based signal representation in non-Gaussian Noise

摘要：

This paper presents a mathematical analysis demonstrating the effectiveness of the signal representation based on Independent Component Analysis (ICA) in the case of non-Gaussian noise corruption.The analysis is based on calculating a mismatch between the distribution of the observed signal represented by a linear model and a reference distribution.The theoretical results lead to a novel ICA-based signal representation technique in which the ICA transformation matrix is estimated based on noisecorrupted signal but not based on clean signal as normal.Our theoretical findings are experimentally demonstrated by employing the proposed feature representation in a GMM-based speaker recognition system.Experimental results show that employment of the proposed ICA-based features can provide significant recognition accuracy improvements over using both the traditional ICA-based features and MFCC features.

作者: Xin Zou Peter Jan(c)ovi(c) M(u)nevver K(o)k(u)er

作者单位: Electronic,Electrical & Computer Engineering,University of Birmingham,Birmingham,UK

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）