um , but was sort of trying to ,  uh , get a general idea  the model  the tree classifier was trying to find general locations that were applicable to different speakers , even though there are huge speaker effects. So. The  but the main limitation now is I  because we 're only looking at things that happen every  ten words or every twenty words , we need more  more data and more data per speaker. So. It 'd also be interesting to look at the EDU meetings because we did include meeting type as a feature , so whether you were in a r Meeting Recorder meeting or a Robustness meeting did matter  to  interrupts because there are just fewer interrupts in the Robustness meetings.
Mm - hmm.
And so the classifier learns more about Morgan than it does about sort of the average person ,
Mm - hmm.