speaker verification with HMM

Hi.
I am trying to write a program to verify the speaker.

I'm confusing with the viterbi algorithm in Hidden Markov Model(HMM). 

As I know, the viterbi algorithm is used to find the best path of the
sequence. 

I would like to know how this algorithm can help when I want to verify
whether the speaker is imposter or not.
[the log likelihood computed is too small. It is around -300 for the true
speaker.]

I would like to know whether I miss some important steps while verifying
the speaker.I found the transition matrix,observation matrix and the
initial state sequence for the training data set and the testing data set.
Then, I found the best path and the probability,p(T) by using Viterbi
algorithm. In Viterbi algorithm, the initial state distribution &
transition matrix that I used are from training data set while the
observation sequence is from the testing data set. Finally,I found log
likelihood=log(p(T)).