Mm - hmm.
eh , because it 's a  a great project. But eh , at the first , in the acoustic , eh , eh , parts of the project , eh I think  you eh  we have eh   two main eh objective. One  one of these is to  eh to detect the change , the acoustic change. And  for that , if you don't use , eh ,  eh , a speech recognizer , eh broad class , or not broad class to  to try to  to    to label the different frames , I think  the Ike criterion  or BIC criterion eh will be enough to detect the change.
OK.
And  Probably.  I  I  I  I would like to  to t prove. Uh , probably. When you you have , eh , eh s eh the transition of speech or  or silence eh to overlap zone , this criterion is enough with   probably with , eh , this kind of , eh , eh the  the  the more eh use eh  use eh  used eh em  normal , regular eh parameter MF - MFCC. you  you have to  to  to find  you can find the  the mark. You can find the  nnn , the  the acoustic change. But eh eh I  I understand that you  your objective is  to eh classify , to know that eh that zone  not is only  a new zone in the  in the file , that eh you have eh , but you have to  to  to know that this is overlap zone. because in the future you will eh try to  to process that zone with a non - regular eh eh speech recognizer model , I suppose.