OK.
Exactly. Yeah. Thank you. And so , uh , I do a  an exhaustive listing of the forms  Actually , I will go through this in  in order , so if  if we could maybe wait and stick keep that for a second cuz we 're not ready for that.
So on the fifth page , seven down
Yeah , yeah , yeah , yeah. Exactly ! Exactly ! Alright so ,  a spelling check first then an exhaustive listing of the , uh  all the forms in the data with the punctuation attached and at that point I pick up things like , oh , you know , word followed by two commas. And th and then another check involves , uh , being sure that every utterance has an identifiable speaker. And if not , then that gets checked. Then there 's this issue of glossing s w so - called " spoken - forms ". So there  mo for the most part , we 're keeping it standard wo word level transcription. But there 's  w And that that 's done with the assumption that  pronunciation variants can be handled. So for things like " and " , the fact that someone doesn't say the " D " , uh that 's not important enough to capture in the transcription because a  a good pronunciation , uh , you know , model would be able to handle that. However , things like " cuz " where you 're lacking an entire very prominent first syllable , and furthermore , it 's a form that 's specific to spoken language , those are r reasons  f for those reasons I  I kept that separate , and used the convention of using " CUZ " for that form , however , glossing it so that it 's possible with the script to plug in the full orthographic form for that one , and a couple of others , not many. So " wanna " is another one , " going  " uh , " gonna " is another one , with just the assumption , again , that this  th these are things which it 's not really fair to a c consider  expect that  a pronunciation model , to handle. And Chuck , you in you indicated that " cuz " is  is one of those that 's handled in a different way also , didn't you ? Did I