Partial Least Squares Based Total Variability Space Modeling for I-Vector Speaker Verification

作     者：CHEN Chen HAN Jiqing 

作者机构：School of Computer Science and Technology Harbin Institute of Technology 

出 版 物：《Chinese Journal of Electronics》 (电子学报(英文))

年 卷 期：2018年第27卷第6期

页      面：1229-1233页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 

基　　金：supported by the National Natural Science Foundation of China(No.61471145 No.91120303) 

主　　题：Speaker verification I-vector Total variability space Partial least squares 

摘      要：As an effective and low-dimension representation for speech utterances with different lengths,i-vector method has drawn considerable attentions in speaker verification. Training a Total variability space(TVS) is one of the key parts in the i-vector method. However, the traditional training method only explores the relationship between different mean supervectors, ignoring priori category information of speakers, which results in a lack of discrimination. In the proposed method, a discriminative TVS based on Partial least squares(PLS) is estimated, in which both the correlation of intra-class and the distinction of inter-class are fully utilized due to using speaker labels, and the proposed method can achieve a better performance.