International Symposium on Chinese Spoken Language Processing
August 23-24, 2002
An improvement of the GMM Speaker Identification Method by Using Two-state HMM and Discriminative Training
Yih-Ru Wang, Shin-Ming Fan
National Chiao Tung University, Hsinchu, Taiwan
In this paper, the GMM-based text-independent speaker
identification system for Mandarin speech is modified by
adding an upper layer to form a two-state HMM system.
The two-state HMM aims at modeling the initial-final
phonetic structure of Mandarin syllables for assisting in
speaker identification. The GPD/MCE training algorithm
is also applied to further improve the system. The
performance of the proposed system was examined by
using a 300-speaker speech database. Error rate reductions
of 25-50% were achieved for the proposed two-state
HMM system over the conventional GMM system.
WANG, Yih-Ru / FAN, Shin-Ming (2002):
"An improvement of the GMM speaker identification method by using two-state HMM and discriminative training",
In ISCSLP 2002, paper 113.