C: And C: Yep .
D: OK .
C: Wonderful .
C: And um we have a little description of asking peop subjects to contact Fey for you know recruiting them for our thing
C: and um there was some confusion as to the consent form , which is basically that that what what you just signed
G: Right .
C: and since we have one already um G: Did Jerry talk to you about maybe using our class ?
G: the students in the undergrad class that he 's teaching ?
C: Um well he said um we definitely " yes " ,
G: e
C: however there is always more people in a in a facul uh in a department than are just taking his class or anybody else 's class at the moment
G: Yeah .
C: and one should sort of reach out and try and get them all .
G: OK , but th I guess it 's that um people in his class cover a different set
G: so G: than the c
G: is the CogSci department that you were talking about ?
D: I guess .
G: uh reaching out to ?
D: See
G: Cuz we have you know people from other areas
D: that 's what I suggested to him , that people like like Jerry and George and et cetera just C: Yeah .
G: advertise in their classes as well .
D: Yeah
D: or even I could you know I could do the actual G: Cuz I mean I I know how to contact our students ,
C: Mm - hmm .
D: That 's generally the way it 's done .
G: so if there 's something that you 're sending out you can also s um send me a copy ,
C: Yeah .
G: me or Bhaskara could either of us could post it to
G: uh
G: is it G: if it 's a general solicitation that you know is just contact you then we can totally pro post it to the news group
D: A mailing list .
C: Mm - hmm .
D: Yeah .
C: Yeah .
G: so .
C: Do it .
D: That 's C: Yeah .
G: OK ,
G: so you 'll send it
G: or something
G: so .
C: As a matter of fact , if you D: I can send it .
D: I 'll send it ,
G: You can send it to me .
C: if G: OK .
D: yeah .
C: Now , i
G: Don't worry ,
G: we this doesn't concern you anymore , Robert .
G: It 's fine .
C: How however I suggest that if you if you look at your email carefully you may think you may find that you already have it .
G: Oops .
G: Already ?
G: Really ?
G: Oops .
D: Probab
C: Maybe .
C: OK .
G: I don't remember getting anything .
C: W we 'll see .
C: Anyhow ,
C: um the uh
C: Yeah , not only
C: Also we will talk about Linguistics and of course Computer Science .
G: Mm - hmm .
C: Um and then , secondly , we had , you may remember , um the problem with the re - phrasing ,
C: that subject always re - phrase sort of the task that uh we gave them ,
B: Right .
C: and so we had a meeting on Friday talking about how to avoid that ,
C: and it proved finally fruitful in the sense that we came up with a new scenario for how to get the the subject m to really have intentions
C: and sort of to act upon those ,
C: and um
C: there the idea is now that next actually we we need to hire one more person to actually do that job
C: because it it 's getting more complicated .
C: So if you know anyone interested in in what i 'm about to describe , tell that person to to write a mail to me or Jerry soon ,
C: fast .
C: Um the idea now is to sort of come up with a high level of sort of abstract tasks
C: " go shopping "
C: um " take in uh a batch of art "
C: um
C: " visit C: do some sightseeing "
C: blah - blah - blah - blah - blah ,
C: sort of analogous to what Fey has started in in in compiling compiling here
C: and already she has already gone to the trouble of of anchoring it with specific um o <comment> um entities and real world places you will find in Heidelberg .
C: And um .
C: So out of these f s these high level categories the subject can pick a couple ,
C: such as if if there is a cop uh a category in emptying your roll of film , the person can then decide " OK , I wanna do that at this place " ,
C: sort of make up their own itinerary a and and tasks
C: and the person is not allowed to take sort of this h high level category list with them ,
C: but uh
C: the person is able to take notes on a map that we will give him and the map will be a tourist 's sort of schematic representation with with symbols for the objects .
C: And so , the person can maybe make a mental note that " ah yeah I wanted to go shopping here "
C: and " I wanted to maybe take a picture of that "
C: and " maybe um eat here "
C: and then goes in and solves the task with the system ,
C: IE <comment> Fey ,
C: and um
C: and we 're gonna try out that C: Any questions ?
G: so um y you 'll have those say somewhere what their intention was G: so you still have the the nice thing about having data where you know what the actual intention was ?
C: Mm - hmm . Yeah .
G: But they will um G: There 's nothing that says you know " these are the things you want to do "
G: so they 'll say " well these are the things I want to do "
G: and G: Right ,
G: so they 'll have a little bit more natural interaction ?
G: OK .
C: Hopefully .
G: Mm - hmm .
F: So they 'll be given this map , which means that they won't have to like ask the system for in for like high level information about where things are ?
C: Yeah it 's a schematic tourist map .
C: So it 'll be uh i it 'll still require the that information
C: and An
G: It w it doesn't have like streets on it that would allow them to figure out their way C: N not not not really the street network .
G: OK .
C: Nuh .
E: So you 're just saying like what part of town the things are in or whatever ?
C: Yeah a
C: and um
C: the map is more a means for them to have the buildings and their names
C: and maybe some ma ma major streets and their names
G: Mm - hmm .
C: and we want to maybe ask them , if you have get it sort of isolated street
C: the the , whatever ,
C: " River Street " ,
C: and they know that they have decided that , yes , that 's where they want to do this kind of action um that they have it with them and they can actually read them
C: or sort of have the label for the object
C: because it 's too hard to memorize all these st strange German names .
C: And then we 're going to have another we 're gonna have w another trial run
C: IE the first with that new setup tomorrow at two
C: and we have a real interesting subject which is Ron Kay
C: for who those who know him , he 's the founder of ICI .
C: So he 'll he 's around seven seventy years old , or something .
G: I didn't know he was the founder .
G: That 's G: OK .
C: And he also approached me and he offered to help um our project
C: and he was more thinking about some high level thinking tasks
C: and I said " sure we need help
C: you can come in as a subject "
C: and he said " OK " .
C: So that 's what 's gonna happen , tomorrow ,
G: Using this new new um plan ,
C: data .
C: New new set up .
G: OK .
C: Yeah .
C: Which I 'll hopefully sort of scrape together t
C: But , thanks to Fey , we already have sort of a nice blueprint and I can work with that .
C: Questions ?
C: Comments on that ?
C: If not , we can move on .
C: No ?
C: No more questions ?
G: So what 's the s this is what you made , Fey ?
E: I 'm not sure I totally understand this
E: but C: Hmm ?
E: I 'm not sure I totally understand everything that 's being talked about
G: Like so So it 's just based on like the materials you had about Heidelberg .
E: but I I imagine I 'll c just catch on .
C: Um are you familiar with with the with the very rough setup of the data ?
D: Based on the web site ,
D: yeah , at the G: Oh OK
G: there 's a web site
G: and then you could like um figure out what the cate
C: experiment ?
D: Right .
E: Uh , this is where they 're supposed to D: It 's a tourist information web site ,
G: OK .
D: so .
G: OK .
C: Talk to a machine and it breaks down and then the human comes on .
E: Yeah .
E: Yeah .
C: The question is just sort of how do we get the tasks in their head that they have an intention of doing something and have a need to ask the system for something without giving them sort of a clear wording or phrasing of the task .
E: OK .
E: OK .
E: OK .
E: OK .
C: Because what will happen then is that people repeat repeat , <comment> or as much as they can , of that phrasing .
G: Hmm .
G: Um , are you worried about being able to identify E: OK .
G: Um .
G: The The goals that we 've d you guys have been talking about are this these you know identifying which of three modes um their question uh concerns .
C: Mm - hmm .
G: So it 's like the Enter versus View C: Yeah , we we we will sort of get a protocol of the prior interaction ,
G: Uh - huh .
C: right ?
C: That 's where the instructor , the person we are going to hire , um and the subjects sit down together with these high level things
G: Uh - huh .
G: Mm - hmm .
C: and so
C: th the q first question for the subject is , " so these are things , you know , we thought a tourist can do .
C: Is there anything that interests you ? "
G: Mm - hmm .
C: And the person can say " yeah , sure sh
C: this is something I would do .
C: I would go shopping " .
C: Yeah ?
G: Mm - hmm .
C: and then we can sort of this s instructor can say " well , uh then you you may want to find out how to get over here
C: because this is where the shopping district is " .
G: So the interaction beforehand will give them hints about how specific or how whatever though the kinds of questions that are going to ask during the actual session ?
C: No .
C: Just sort of OK , what what what would you like to buy
C: and then um OK there you wanna buy a whatever cuckoos clocks
G: Yeah .
C: OK and the there is a store there .
E: Mm - hmm .
C: So the task then for that person is t finding out how to get there ,
G: Mm - hmm .
C: right ?
C: That 's sort of what 's left .
G: Mm - hmm .
C: And we know that the intention is to enter because we know that the person wants to buy a cuckoos clock .
G: OK , that 's what I mean
G: so like those tasks are all gonna be um unambiguous about which of the three modes .
C: Hopefully .
G: Right . OK .
G: So .
A: Well , so the idea is to try to get the actual phrasing that they might use and try to interfere as little as possible with their choice of words .
C: Hopefully .
G: t            That they 'll be here ?
C: Yes . In a sense that 's exactly the the the idea ,
A: uh uh
C: which is never possible in a in a s in a lab situation ,
A: Well , u u the one experiment th that that that I 've read somewhere , it was they u used pictures .
C: nuh ?
C: Yep .
E: Mm - hmm .
A: So to to uh actually um uh specify the the tasks .
A: Uh , but you know i i
C: Yeah .
C: We had exactly that on our list of possible way things
C: so we uh I even made a sort of a silly thing how that could work , how you control you are here
C: you you want to know how to get someplace ,
C: and this is the place
C: and it 's a museum
C: and you want to do some
C: and and and there 's a person looking at pictures .
C: So , you know , this is exactly getting someplace with the intention of entering and looking at pictures .
A: Right .
C: However , not only was the common census were among all participants of Friday 's meeting was it 's gonna be very laborious to to make these drawings for each different things ,
C: all the different actions , if at all possible ,
A: Right .
C: and also people will get caught up in the pictures .
C: So all of a sudden we 'll get descriptions of pictures in there .
A: Right .
C: And people talking about pictures and pictorial representations
E: Hmm .
C: and um
A: Right .
C: I would s I would still be willing to try it .
A: I mean , I I 'm I 'm not saying it 's necessary
A: but but uh i uh uh i you might be able to combine you know text uh and and some sort of picture
A: and also uh I think it it will be a good idea to show them the text and kind of chew the task
A: and then take the test away the the the the the text away
C: Mm - hmm .
C: Yeah .
A: so that they are not uh guided by by by what you wrote ,
C: We will A: but can come up with their with their own C: Yeah ,
C: they will have no more linguistic matter in front of them when they enter this room .
A: Right .
C: OK .
C: Then I suggest we move on to the to
C: we have um uh the EDU Project ,
C: let me make one more general remark , has sort of two two side uh um actions , its um action items that we 're do dealing with ,
C: one is modifying the SmartKom parser and the other one is modifying the SmartKom natural language generation module .
C: And um this is not too complicated
C: but I 'm just mentioning it C: put it in the framework
C: because this is something we will talk about now .
C: Um , I have some news from the generation ,
C: do you have news from the parser ?
F: Um , not C: By that look I F: Yes , uh , I would really p It would be better if I talked about it on Friday .
C: OK .
F: If that 's OK .
C: Yeah ,
C: wonderful .
C: Um , did you run into problems or did you run into not h having time ?
F: Yeah .
F: But not not any time part .
C: OK , so that 's good .
C: That 's better than running into problems .
F: OK .
C: And um I I do have some good news for the natural language generation however .
C: And the good news is I guess it 's done .
C: Uh , meaning that Tilman Becker , who does the German one , actually took out some time and already did it in English for us .
C: And so the version he 's sending us is already producing the English that 's needed to get by in version one point one .
F: So I take it that was similar to the what what we did for the parsing ?
C: Yeah .
C: I I it even though the generator is a little bit more complex
C: and it would have been , not changing one hundred words but maybe four hundred words ,
F: OK .
C: but it would have been
F: OK .
C: but this this is I guess good news ,
C: and the uh the time
C: and especially Bhaskara
C: and uh and um C: Oh do I have it here ?
C: No .
C: The time is now pretty much fixed .
C: It 's the last week of April until the fourth of May
C: so it 's twenty - sixth through fourth . That they 'll be here .
C: So it 's it 's extremely important that the two of you are also present in this town during that time .
B: Wait , what what are the days ?
B: April twenty - sixth to the May fourth ?
C: Yeah , something like that .
B: I 'll probably be here .
F: Yeah .
C: It 's E: You will be here .
C: There is a d
C: Isn't finals coming up then pretty much after that ?
F: Finals was that .
G: Yeah w it doesn't really have much meaning to grad students
G: but final projects might .
C: OK .
F: Yeah actually , that 's true .
G: That C: Anyway , so this is B: Well I 'll be here working on something .
B: Guaranteed ,
B: it 's just uh will I be here , you know , in
B: uh B: I 'll be here too actually
B: but A: Hmm .
C: No it 's just um you know they 're coming for us so that we can bug them
G: Ye
C: and ask them more questions
C: and sit down together
C: and write sensible code
C: and they can give some nice talks and stuff .
C: But uh
C: just make a B: But it 's not like we need to be with them twenty - four hours a day s for the seven days that they 're here .
C: Not not unless you really really want to .
E: They 're very dependent
C: Not unless you really want to .
C: And they 're both nice guys
C: so you may may want to .
C: OK , that much from the parser and generator side ,
C: unless there are more questions on that .
G: So , no sample generator output yet ?
C: No .
G: OK .
C: It Just a mail that , you know , he 's sending me the the the stuff soon
G: This is being sent ,
G: mm - hmm .
G: OK .
G: Mm - hmm .
C: and I was completely flabbergasted here
C: and I and that 's also it 's it 's going to produce the concept - to - speech uh blah - blah - blah information for necessary for one point one in English C: based on the English ,
C: you know , in English .
C: So .
C: I was like " OK ,
E: We 're done .
C: we 're done ! "
G: So that was like one of the first l You know , the first task was getting it working for English .
G: So that 's basically over now .
G: Is that right ?
C: Yeah .
G: So the basic requirement fulfilled .
C: Um , the basic requirement is fulfilled almost .
C: When Andreas Stolcke and and his gang ,
G: Mm - hmm .
C: when they have um changed the language model of the recognizer and the dictionary , then we can actually a put it all together
G: Mm - hmm .
G: So the speech recognizer also works .
G: Uh - huh .
G: Mm - hmm .
C: and
C: you can speak into it and ask for TV and movie information
E: Toll .
C: and then when
C: if if something actually happens and some answers come out , then we 're done .
G: Mm - hmm .
G: If and they 're kind of correct .
E: So it 's not done basically .
C: Hmm ?
G: And they kind of are are correct .
E: Right .
G: It 's not just like anything .
E: Perhaps if the answers have something to do with the questions for example .
G: And they 're mostly in English .
G: So .
C: Then um G: Are they is it using the database ?
G: the German TV movie .
C: Yeah .
G: OK .
G: So all the actual data might be German names ?
C: Um well actually th um
G: Or are they all like American TV programs ?
C: um well E: I want to see " Die Dukes Von Hazard "
C: The C: OK , so you don't know how the German dialogue uh the German the demo dialogue actually works .
C: It works C: the first thing is what 's , you know , showing on TV ,
C: and then the person is presented with what 's running on TV
C: in Germany on that day , on that evening
G: Mm - hmm ,
G: mm - hmm .
C: and so you take one look at it and then you say " well that 's really nothing there 's nothing for me there "
C: " what 's running in the cinemas ? "
G: Mm - hmm .
C: So maybe there 's something better happening there .
C: And then you get you 're shown what movies play which films ,
C: and it 's gonna be of course all the Heidelberg movies and what films they are actually showing .
G: Mm - hmm .
C: And most of them are going to be Hollywood movies .
G: Hmm .
C: So , " American Beauty " is " American Beauty " ,