  In some speaker recognition scenarios we find conversations recorded
simultaneously over multiple channels. That is the case of the interviews in
the NIST SRE dataset. To take advantage of that, we propose a modification of
the PLDA model that considers two different inter-session variability terms.
The first term is tied between all the recordings belonging to the same
conversation whereas the second is not. Thus, the former mainly intends to
capture the variability due to the phonetic content of the conversation while
the latter tries to capture the channel variability. In this document, we
derive the equations for this model. This model was applied in the paper
"Handling Recordings Acquired Simultaneously over Multiple Channels with PLDA"
published at Interspeech 2013.
