0
$\begingroup$

This question refers to the following paper:

Support Vector Machines for Speaker and Language Recognition, W. M. Campbell, J. P. Campbell, D. A. Reynolds, E. Singer, P. A. Torres-Carrasquillo, Computer speech and Language 20 (2006) 210-229.

I am trying to implement the algorithm in table 1 and table 2 in page 18. In step 6 of of table 1 they are calculating $b_z^i$ as a mean (or sum) of $b(z_i)$ and number of entries is $N_z$ which they claim to be the number of features.

The question is what is $N_z$ here. As I understand each feature set, which is of dimension $N_z$, has been used to create $b(z_i)$, so what this summation means? One can only sum over time dimension, which has nothing to do $N_z$. $N_z$ is kind of spatial dimension as one time frame of data is converted to features.

$\endgroup$
0
$\begingroup$

$N_z$ is number of frames in the utterance, it is exactly time dimension. Instead "number of features" they should say "number of feature vectors".

$\endgroup$
  • $\begingroup$ Thanks a lot. I have implemented exactly like that. Thanks. $\endgroup$ – Creator Apr 18 at 23:11

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.