Speaker identification using time-delay HMEs.
In this paper, we extend the Hierarchical Mixture of Experts (HME) to temporal processing and explore it for a substantial problem, that of text-dependent speaker identification. For a specific multiway classification, we propose a generalized Bernoulli density instead of the multinomial logit density to avoid the instability during training. Time-delay technique is applied for spatio-temporal processing in the HME and a combining scheme is presented for combining multiple time-delay HMEs in order to complete a multi-scale analysis for the temporal data. Using the time-delay HME along with the EM algorithm as well as the combination of multiple time-delay HMEs, the speaker identification system has a good performance and yields significantly fast training. We have also addressed some issues about the time-delay techniques in the HME.
Chen
K
K
National Lab of Machine Perception, Peking University, Beijing, China.
Xie
D
D
Chi
H
H
D000465:Algorithms; D016010:Binomial Distribution; D006801:Humans; D015233:Models, Statistical; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D013060:Speech; D013995:Time; D014831:Voice