C: Now can you give me the uh remote T ?
D: OK , so Eva , co uh could you read your numbers ?
A: Go ahead and read .
D: Yeah .
A: OK .
C: Alright .
D: Yeah , let 's get started .
D: Um Hopefully Nancy will come ,
D: if not , she won't .
B: Uh , Robert , do you uh have any way to turn off your uh screensaver on there so that it 's not going off every uh ,
B: it seems to have about at two minute C: Yeah , I 've I uh it 's not that I didn't try .
B: OK .
C: and um I I told it to stay on forever and ever , but if it 's not plugged in it just doesn't obey my commands .
B: OK .
C: It has a mind .
B: Got it .
E: Wants to conserve .
C: But I I just You know , sort of keep on wiggling .
B: Yeah , OK .
C: But uh we 'll just be m m working on it at intensity so it doesn't happen .
C: We 'll see .
C: Should we plunge right into it ?
D: Yeah .
C: So , would you like to D: I think so .
C: So what I 've tried to do here is list all the decision nodes that we have identified on this side .
C: Commented and what they 're about and sort of the properties we may um give them .
C: And here are the uh tasks to be implemented via our data collection .
C: So all of these tasks C: The reading is out of these tasks more or less imply that the user wants to go there , sometime or the other .
C: And analogously for example , here we have our EVA um intention .
C: And these are the data tasks where w we can assume the person would like to enter , view or just approach the thing .
C: Analogously the same on the object information
C: we can see that , you know , we have sort of created these tasks before we came up with our decision nodes
C: so there 's a lot of things where we have no analogous tasks , and that may or may not be a problem .
C: We can change the tasks slightly if we feel that we should have data for e sort of for every decision node
C: so trying to im um implant the intention of going to a place now , going to a place later on the same tour ,
C: or trying to plant the intention of going sometime on the next tour , or the next day or whenever .
D: Right , right .
C: But I think that might be overdoing it a little .
D: So Yeah .
D: So let me pop up a level .
D: And uh s s make sure that we 're all oriented the same .
D: So What we 're gonna do today is two related things .
D: Uh one of them is to work on the semantics of the belief - net which is going to be the main inference engine for thi the system uh making decisions .
D: And decisions are going to turn out to be parameter choices for calls on other modules .
D: so f the natural language understanding thing is uh , we think gonna only have to choose parameters , but You know , a fairly large set of parameters .
D: So to do that , we need to do two things .
D: One of which is figure out what all the choices are , which we 've done a fair amount .
D: Then we need to figure out what influences its choices
D: and finally we have to do some technical work on the actual belief relations and presumably estimates of the probabilities and stuff .
D: But we aren't gonna do the probability stuff today .
D: Technical stuff we 'll do uh another day .
D: Probably next week .
D: But we are gonna worry about all the decisions and the things that pert that contribute to them .
D: And we 're also , sort of uh in the same process , going to work with Fey on what there should be in the dialogues .
D: So One of the s steps that 's coming up real soon is to actually get subjects uh in here , and have them actually record like this .
D: Uh record dialogues more or less .
D: And depending on what Fey sort of provokes them to say , we 'll get information on different things .
D: So C: Well how people phrase different intentions more or less ,
D: Fo - v yeah people with the phrase them
C: huh ?
D: and so Uh for , you know , Keith and people worrying about what constructions people use , uh we have some i we have some ways to affect that by the way the dialogues go .
D: So what Robert kindly did , is to lay out a table of the kinds of uh things that that might come up ,
D: and , the kinds of decisions .
D: So the uh uh on the left are decision nodes , and discreet values .
D: So if if we 're right , you can get by with um just this middle column worth of decisions ,
D: and it 's not all that many , and it 's perfectly feasible technically to build belief - nets that will do that .
D: And he has a handout .
C: Yeah .
C: Maybe it was too fast plunging in there , because j we have two updates .
D: Yeah .
C: Um you can look at this if you want ,
C: these are what our subject 's going to have to fill out .
C: Any comments I can can still be made and the changes will be put in correspondingly .
E: m      Yes .
C: Let me summarize in two sentences ,
C: mainly for Eva 's benefit , who probably has not heard about the data collection , at all .
A: OK .
C: Or have you heard about it ?
A: Not that much
C: No .
A: you didn't .
C: OK . We were gonna put this in front of people .
C: They give us some information on themselves .
A: OK .
C: Then then they will read uh a task where lots of German words are sort of thrown in between .
C: And um and they have to read isolated proper names
C: And these change D: S I don't see a release
C: No , this is not the release form .
C: This is the speaker information form .
D: Got it .
D: OK , fine .
D: OK .
C: The release form is over there in that box .
D: Alright , fair enough .
C: And um And then they gonna have to f um um choose from one of these tasks , which are listed here .
C: They they pick a couple ,
C: say three uh uh six as a matter of fact .
C: Six different things they sort of think they would do if they were in Heidelberg or traveling someplace C: and um and they have a map .
B: Hmm .
C: Like this .
C: Very sketchy , simplified map .
C: And they can take notes on that map .
C: And then they call this computer system that works perfectly , and understands everything .
A: OK .
C: And um C: The comp Yeah , the computer system sits right in front of you ,
B: This is a fictional system obviously ,
B: huh .
C: that 's Fey .
E: I 've I understand everything .
D: And she does know everything .
E: Yes I do .
C: And she has a way of making this machine talk .
C: So she can copy sentences into a window , or type really fast
C: and this machine will use speech synthesis to produce that .
C: So if you ask " How do I get to the castle " then a m s several seconds later it 'll come out of here " In order to get to the castle you do "
C: OK ?
B: Yeah .
C: And um And then after three tasks the system breaks down .
C: And Fey comes on the phone as a human operator .
C: And says " Sorry the system broke down but let 's continue . "
C: And we sort of get the idea what people do when they s think they speak to a machine and what people say when they think they speak to a human , or know , or assume they speak to a human .
A: OK .
A: Huh .
B: Mm - hmm .
B: Mm - hmm .
C: That 's the data collection .
C: And um And Fey has some thirty subjects lined up ?
C: Something ?
E: Yeah .
E: And more and more every day .
C: And um And they 're r ready uh to roll .
C: And we 're gonna start tomorrow at three ?
C: four ?
C: one ?
E: Tomorrow ,
E: well we don't know for sure .
E: Because we don't know whether that person is coming or not ,
C: OK .
E: but C: Around four - ish .
C: And um we 're still l looking for a room on the sixth floor because they stole away that conference room . Um behind our backs .
C: But D: Well , there are these uh uh D: oh , I see , we have to D: Yeah , it 's tricky .
D: We 'll let 's let we 'll do that off - line , OK .
C: Yeah , but I i i it 's happening .
C: David and and Jane and and Lila are working on that as we speak .
D: OK .
C: OK .
C: That was the uh the data collection in a nutshell .
C: And um I can report a so I did this but I also tried to do this C: so if I click on here ,
C: Isn't this wonderful ?
C: we get to the uh uh belief - net just focusing on on the g Go - there node .
C: uh Analogously this would be sort of the reason node and the timing node and so forth .
B: Mm - hmm .
C: And what w what happened is that um design - wise I 'd sort of n noticed that we can we still get a lot of errors from a lot of points to one of these sub Go - there User Go - there Situation nodes .
C: So I came up with a couple of additional nodes here where um
C: whether the user is thrifty or not , and what his budget is currently like , is going to result in some financial state of the user .
C: How much will he is he willing to spend ?
C: Or can spend .
C: Being the same at this just the money available , which may influence us , whether he wants to go there
C: if it is you know charging tons of dollars for admission or its gonna g cost a lot of t e
C: whatever .
C: Twenty - two million to fly to International Space Station , you know .
D: Right .
C: just Not all people can do that .
C: So , and this actually turned out to be pretty key , because having specified sort of these uh this this intermediate level Um and sort of noticing that everything that happens here C: let 's go to our favorite endpoint one
C: is again more or less we have um C: then the situation nodes contributing to the the endpoint situation node , which contributes to the endpoint and so forth .
C: um I can now sort of draw straight lines from these to here , meaning it g of course goes where the sub - S C: everything that comes from situation , everything that comes from user goes with the sub - U ,
C: and whatever we specify for the so - called " Keith node " , or the discourse , what comes from the um parser , construction parser , um will contribute to the D and the ontology to the sub - O node .
C: And um one just s sort of has to watch which also final decision node so it doesn't make sense t to figure out whether he wants to enter , view or approach an object if he never wants to go there in the first place .
C: But this makes the design thing fairly simple .