ADAPTIVE BACKGROUND MODEL DESIGN FOR DISTANT SPEAKER VERIFICATION SYSTEM OVER THE TELEPHONE

Most stateoftheart speaker verification systems need a speaker independent(SI) background model,and use some adaptive method to train the background model.But these systems rely heavily on the consistency of acoustic conditions under which the SI models were trained.These constraints may be a burden in practical verification system such as using telephone set or wireless handsets which place a premium on the time on enrolling and verifing.Also,using all speaker's data to train the global background model need so much time.In this paper,we present a reliable approach to background model design that only need the enrollment data during the speaker training and verification,then remodeling the background model when the system is free,and using some improved adaptive method to remodeling the global model.Results are provided to demonstrate the effectiveness of such systems.