双向二维加权LPP语音特征降维算法  

Research on(2D)2WLPP for Speech Feature Vector Reducion

作　　者：齐晓倩[1] 陈鸿昶[1] 黄海[1] 

机构地区：[1]解放军信息工程大学信息工程学院,郑州450002

出　　处：《小型微型计算机系统》2012年第7期1588-1591,共4页Journal of Chinese Computer Systems

基　　金：国家"八六三"高技术研究发展计划项目(2008AA011002)资助

摘　　要：提出一种双向二维加权局部保持投影算法(Two-directional Two-dimensional Weighted Locality Preserving Projections,(2D)2WLPP)用于语音特征提取后维度的降低,考虑到普通的二维降维算法只能从一个方向进行特征降维且所降至的维数选择非常受限,该方法能够从水平和垂直两个方向对语音矩阵进行降维处理,这样可以大大降低提取后的语音特征数目;考虑到不同投影向量对保持局部结构的重要程度不同,进而对各个特征赋予不同的权重系数.实验证明,该算法运算速度快,与已有的二维局部保持投影相比,获得了更高的识别率.A novel Two-directional Two-dimensional Weighted Locality Preserving Projections（（2D）2WLPP）,which can effectively reduce feature dimension is applied to speech feature extraction.Feature matrix is obtained by reducing speech matrix horizontally and vertically,while common two-dimensional reduction method can only reduce the dimension by one direction.Considering that projecting vectors are not of the same importance to preserve local structure,different vectors are given different values.Experimental result shows that this algorithm is efficient and can achieve higher recognition rate than 2DLPP.

关 键 词：语音特征 二维局部保持投影 双向二维加权局部保持投影 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]