D: And so I 'm just in in progress of , yeah , trying to feed the recognizer with un - segmented data
D: and to see how much worse that is .
D: So that that I have three things .
D: Un - yeah un - segmented , the automatic , and the the ideal one .
C: Yeah .
G: But the recognizer 's putting up some resistance
G: because it doesn't like the un - segmented data .
D: Yeah .
C: Uh - huh .
H: Um . Yeah , I just got back from Chicago .
H: So .
H: Um , fishing went pretty well .
F: Oh , yeah . All of us are banging .
C: Good . Good .
H: And , um , I was gonna post some results , you know , with , uh ,
B: Wisconsin fishing .
F: With fishing . B
H: Wisconsin fishing . Yeah .
C: Yeah .
H: Uh .
C: So your so your results are about the same as Bush 's ,
F: You should have seen the one that got away .
C: basically . His H: Y who Yeah , right .
H: Whose result ?
C: Bush 's .
C: Yeah , you 're both , you know , sort of He 's he 's coming back to the heartland
C: and H: Yeah , right , exactly .
H: I did my tour of the heartland .
C: Right . Yeah .
I: Did you build any houses ?
H: Yeah .
H: Yeah . I built a few built a few houses .
H: Um ,
H: but right now I guess , uh , I 'm working on this paper this ISCA paper for this workshop that Liz and Andreas and I are putting together .
H: So we 're just getting , uh , different results for H: Um , we fixed up our different , uh , transcripts with different types of , uh , annotations
H: and we re re - ran ali re - ran alignments .
H: And we 're gonna develop a new feature database based on those alignments
H: and do some trees and analysis .
H: So I 'm kind of in the middle of that .
H: And
H: hopefully by the twentieth , the twenty - third .
B: Twentieth .
H: The twentieth !
H: Yeah . We 'll have it all straightened out .
G: Yeah .
H: So . It 's gonna be a busy week .
G: Yeah .
G: You know , I 'll bet You know , Bush went on this European trip recently
G: and they told him there that they get more vacations .
C: Yeah .
G: So he came back here and thought " oh , I I can afford some more vacation too " .
B: Beep .
C: Yeah . I I think he 's b he 's been he will have been off , like , two months out of his first seven in office .
H: Yeah . It 's amazing .
G: Yeah . It 's hard to keep concentration , you know ,
C: That 's a pretty good deal .
G: and the focus on the I: Don't even really notice ,
I: do you ?
C: Anyway .
G: Um .
G: So while he 's vacationing , um , we 've been , uh G: Well basically this is like a joint effort .
G: Uh , d we were just C: Who are you talking about ,
C: Bush or Don ?
C: Yeah .
G: Um ,
G: you know , f apart from getting preparing the the da the data for the ,
G: um  for these experiments for the , um , uh for this prosody workshop ,
G: um , we just , um we just had a phone call with Mari and her students , in fact ,
G: and they want to , um , e m They 're bringing up their own meeting recognizer ,
G: which is based on Bill Byrne 's , uh , recognizer from Johns Hopkins .
C: Mm - hmm .
C: Based on Hub - five , or like like your ?
G: u <comment> Based on their Hub - five recognizer .
B: Mm - hmm .
G: And , uh ,
C: Yeah .
G: so they 've been getting from us the , um  you know , some support in terms of getting the latest transcripts
G: and the also the actually the , uh , transcripts annotated with events ,
C: Mm - hmm .
G: uh , like sentence boundaries and stuff like that .
C: Mm - hmm .
C: Yeah .
G: Um , because one of Mari 's students was to wants to do some language modeling for , uh , predicting overlaps and , uh , stuff like that .
C: Yeah .
G: Um .
B: Yeah . Actually we had this ide from the last time that they were here , that it 'd be nice to have UW do some work on language modeling that would be trying to get at the same detection as what we do acoustically
F: Can I borrow a piece of paper ?
B: since they can ramp up much ques quicker in the language modeling
F: Thank you .
B: and we don you know , we 'll do the , uh , prosodic side .
B: And so this is supposed to be a project that we could actually integrate the posteriors that they get from their language model for every word boundary or every frame boundary ,
B: and then train up the classifiers .
C: Yeah .
G: Mm - hmm .
B: And it 's I guess it 's an undergrad , too , that that 's going to be doing this work .
H: Cool .