Recognition correct rate and noise robust property are indeed important for speaker recognition research

but the response rate of recognition is also a key factor for a speaker recognition system when applied in the real world.Owing to this

we propose a novel speaker identification approach based on speaker clustering

namely Hierarchical Speaker Identification (HSI).It can increase the running speed greatly for speaker identification systems

and the more the number of registered speakers is

the faster the HSI system runs than the Conventional Speaker Identification (CSI) system.Simultaneously

its counterpart for speaker verification based on speaker clustering

can reduce the rates of false rejection and false acceptance efficiently to improve the capability of verification.A new method is also presented here called reliability scoring.The experiments show that speaker clustering based algorithms can run faster 3.5 times than original approach for the speaker identification and is 53.75% deduction of equal or minimal error rates for the speaker verification on average.