elplaguister/DTS_line_datasets · Datasets at Hugging Face

topic_shift bool 2 classes	utterance stringlengths 1 7.9k	session_id stringlengths 7 14
false	Yeah.	QMSum_51
false	Um then celebration.	QMSum_51
false	Celebration.	QMSum_51
false	Cel celebration yes , yes.	QMSum_51
false	Ah.	QMSum_51
false	Today we have apple juice and after we sell m million of 'em we have champagne.	QMSum_51
false	So I I thank you all very much. Um , I think this was very good and um	QMSum_51
false	Yeah.	QMSum_51
false	Mm-hmm.	QMSum_51
false	I think we did come up with a new product that's uh feasible. Feasible from the production point of view and feasible from a marketing point of view.	QMSum_51
false	Mm-hmm. Mm-hmm.	QMSum_51
false	So , thank you.	QMSum_51
false	Okay.	QMSum_51
false	Yeah.	QMSum_51
false	Thank you.	QMSum_51
false	Thank you very much.	QMSum_51
false	Okay. Watch I I have my cord behind you here.	QMSum_51
false	Okay.	QMSum_51
false	Okay.	QMSum_51
false	I always get it on here , but getting it off is	QMSum_51
false	Do we do we have some time left ? Uh you have	QMSum_51
false	They say it's forty minutes.	QMSum_51
false	Ah yes we have time later	QMSum_51
false	But we we were told we could end the final meeting at any time , whenever we felt we were finished.	QMSum_51
false	but we don't	QMSum_51
false	Okay.	QMSum_51
false	Oh , alright.	QMSum_51
false	It'll take me the rest of the time to get my microphone out from my necklace. Oh , there we go.	QMSum_51
false	Why ?	QMSum_45
false	Um.	QMSum_45
false	I 'm known. I	QMSum_45
false	No , cuz she already told me it , before she told you.	QMSum_45
false	No , she told me a long time ago. She told me she told me like two weeks ago.	QMSum_45
false	Oh , well , it doesn't matter what time.	QMSum_45
false	OK. You know how to toggle the display width function	QMSum_45
false	Well maybe she hadn't just started transcribing me yet.	QMSum_45
false	Wow.	QMSum_45
false	Anyway.	QMSum_45
false	What is it ?	QMSum_45
false	Let me explain something to you.	QMSum_45
false	Um ,	QMSum_45
false	My laugh is better than yours.	QMSum_45
false	there.	QMSum_45
false	I beg to differ.	QMSum_45
false	Yo.	QMSum_45
false	Um , OK.	QMSum_45
false	But you have to say something genuinely funny before you 'll get an example.	QMSum_45
false	Yeah.	QMSum_45
false	The thing is I don't know how to get to the next page. Here.	QMSum_45
false	No. You should be at least be self - satisfied enough to laugh at your own jokes.	QMSum_45
false	Actually I thought	QMSum_45
false	No , it 's a different laugh.	QMSum_45
false	There.	QMSum_45
false	Ooh , wow !	QMSum_45
false	How weird.	QMSum_45
false	Oh ! Holy mackerel.	QMSum_45
false	Wow. Whoa !	QMSum_45
false	What ? ! Oh. OK. I wasn't even doing anything. OK.	QMSum_45
false	Uh.	QMSum_45
false	Eva 's got a laptop , she 's trying to show it off.	QMSum_45
false	That was r actually Robert 's idea. But anyhow. Um	QMSum_45
false	O K. So , here we are.	QMSum_45
false	Once again.	QMSum_45
false	Once again , right , together. Um , so we haven't had a meeting for a while , and and probably won't have one next week , I think a number of people are gone. Um , so Robert , why don't you bring us up to date on where we are with EDU ?	QMSum_45
false	Um , uh in a in a smaller group we had uh , talked and decided about continuation of the data collection. So Fey 's time with us is almost officially over , and she brought us some thirty subjects and , t collected the data , and ten dialogues have been transcribed and can be looked at. If you 're interested in that , talk to me. Um , and we found another uh , cogsci student who 's interested in playing wizard for us. Here we 're gonna make it a little bit more complicated for the subjects , uh this round. She 's actually suggested to look um , at the psychology department students , because they have to partake in two experiments in order to fulfill some requirements. So they have to be subjected , before they can actually graduate. And um , we want to design it so that they really have to think about having some time , two days , for example , to plan certain things and figure out which can be done at what time , and , um , sort of package the whole thing in a in a re in a few more complicated um , structure. That 's for the data collection. As for SmartKom , I 'm the last SmartKom meeting I mentioned that we have some problems with the synthesis , which as of this morning should be resolved. And , so ,	QMSum_45
false	Good.	QMSum_45
false	" should be " means they aren't yet , but but I think I have the info now that I need. Plus , Johno and I are meeting tomorrow , so maybe uh uh , when tomorrow is over , we 're done. And ha n hav we 'll never have to look at it again Maybe it 'll take some more time , to be realistic , but at least we 're we 're seeing the end of the tunnel there. That was that. Um , the uh , uh I don't think we need to discuss the formalism that 'll be done officially s once we 're done. Um , something happened , in on Eva 's side with the PRM that we 're gonna look at today , and um , we have a visitor from Bruchsal from the International University. Andreas , I think you 've met everyone except Nancy.	QMSum_45
false	Sorry. Hi. Hi.	QMSum_45
false	Yeah.	QMSum_45
false	Hi. Hi.	QMSum_45
false	So when you said " Andreas " I thought you were talking about Stolcke.	QMSum_45
false	And , um ,	QMSum_45
false	Now I know that we aren't , OK.	QMSum_45
false	Andy , you actually go by Andy , right ? Oh , OK.	QMSum_45
false	Yeah.	QMSum_45
false	Eh	QMSum_45
false	Cuz there is another Andreas around ,	QMSum_45
true	Hmm.	QMSum_45
false	so , to avoid some confusion.	QMSum_45
false	That will be Reuter ? Oh , OK.	QMSum_45
false	Yeah.	QMSum_45
false	So my scientific director of the EML is also the dean of the International University , one of his many occupations that just contributes to the fact that he is very occupied. And , um , the um , he @ @ might tell us a little bit about what he 's actually doing , and why it is s somewhat related , and by uh using maybe some of the same technologies that we are using. And um. Was that enough of an update ?	QMSum_45
false	I think so.	QMSum_45
false	In what order shall we proceed ?	QMSum_45
false	OK.	QMSum_45
false	Maybe you have your on - line	QMSum_45
false	Uh , yeah , sure. Um , so , I 've be just been looking at , um , Ack ! What are you doing ? Yeah. OK. Um , I 've been looking at the PRM stuff. Um , so , this is , sort of like the latest thing I have on it , and I sorta constructed a couple of classes. Like , a user class , a site class , and and you know , a time , a route , and then and a query class. And I tried to simplify it down a little bit , so that I can actually um , look at it more. It 's the same paper that I gave to Jerry last time. Um , so basically I took out a lot of stuff , a lot of the decision nodes , and then tried to The red lines on the , um , graph are the um , relations between the different um , classes. Like , a user has like , a query , and then , also has , you know um , reference slots to its preferences , um , the special needs and , you know , money , and the user interest. And so this is more or less similar to the flat Bayes - net that I have , you know , with the input nodes and all that. And So I tried to construct the dependency models , and a lot of these stuff I got from the flat Bayes - net , and what they depend on , and it turns out , you know , the CPT 's are really big , if I do that , so I tried to see how I can do , um put in the computational nodes in between. And what that would look like in a PRM. And so I ended up making several classes Actually , you know , a class of with different attributes that are the intermediate nodes , and one of them is like , time affordability money affordability , site availability , and the travel compatibility. And so some of these classes are s some of these attributes only depend on stuff from , say , the user , or s f just from , I don't know , like the site. S like , um , these here , it 's only like , user , but , if you look at travel compatibility for each of these factors , you need to look at a pair of , you know , what the um , preference of the user is versus , you know , what type of an event it is , or you know , which form of transportation the user has and whether , you know , the onsite parking matters to the user , in that case. And that makes the scenario a little different in a PRM , because , um , then you have one - user objects and potentially you can have many different sites in in mind. And so for each of the site you 'll come up with this rating , of travel compatibility. And , they all depend on the same users , but different sites , and that makes a I 'm tr I w I wa have been trying to see whether the PRM would make it more efficient if we do inferencing like that. And so , I guess you end up having fewer number of nodes than in a flat Bayes - net , cuz otherwise you would c well , it 's probably the same. But um , No , you would definitely have be able to re - use , like , um , all the user stuff , and not not having to recompute a lot of the stuff , because it 's all from the user side. So if you changed sites , you you can , you know , save some work on that. But , you know , in the case where , it depends on both the user and the site , then I 'm still having a hard time trying to see how um , using the PRM will help. Um , so anyhow , using those intermediate nodes then , this this would be the class that represent the intermediate nodes. And that would basically it 's just another class in the model , with , you know , references to the user and the site and the time. And then , after you group them together this no the dependencies would of the queries would be reduced to this. And so , you know , it 's easier to specify the CPT and all. Um , so I think that 's about as far as I 've gone on the PRM stuff.	QMSum_45
false	Well	QMSum_45
false	Right.	QMSum_45
false	No. So y you didn't yet tell us what the output is.	QMSum_45
false	The output.	QMSum_45
false	So what decisions does this make ?	QMSum_45
false	OK. So it only makes two decisions , in this model. And one is basically how desirable a site is meaning , um , how good it matches the needs of a user. And the other is the mode of the visit , whether th It 's the EVA decision. Um , so , instead of um , doing a lot of , you know , computation about , you know , which one site it wants of the user wants to visit , I 'll come well , try to come up with like , sort of a list of sites. And for each site , you know , where h how how well it fits , and basically a rating of how well it fits and what to do with it. So. Anything else I missed ?	QMSum_45
false	So that was pretty quick. She 's ac uh uh Eva 's got a little write - up on it that uh , probably gives the the details to anybody who needs them. Um , so the You you didn't look at all yet to see if there 's anybody has a implementation.	QMSum_45
false	No , not yet , um	QMSum_45
false	OK. So one so one of the questions , you know , about these P R Ms is	QMSum_45
false	Mm - hmm.	QMSum_45
false	uh , we aren't gonna build our own interpreter , so if if we can't find one , then we uh , go off and do something else and wait until s one appears. Uh , so one of the things that Eva 's gonna do over the next few weeks is see if we can track that down. Uh , the people at Stanford write papers as if they had one , but , um , we 'll see. So w Anyway. So that 's a a major open issue. If there is an interpreter , it looks like you know , what Eva 's got should run and we should be able to actually um , try to solve , you know , the problems , to actually take the data , and do it. Uh , and we 'll see. Uh , I actually think it is cleaner , and the ability to instantiate , you know , instance of people and sites and stuff , um , will help in the expression. Whether the inference gets any faster or not I don't know. Uh , it wouldn't surprise me if it if it doesn't.	QMSum_45
false	Mm - hmm.	QMSum_45
false	You know , it 's the same kind of information. I think there are things that you can express this way which you can't express in a normal belief - net , uh , without going to some incredible hacking of sort of rebuilding it on the fly. I mean , the notion of instantiating your el elements from the ontology and stuff fits this very nicely and doesn't fit very well into the extended belief - net. So that was one of the main reasons for doing it. Um. I don't know. So , uh , people who have thought about the problem , like Robert i it looked to me like if Eva were able to come up with a you know , value for each of a number of uh , sites plus its EVA thing , that a travel planner should be able to take it from there. And you know , with some other information about how much time the person has and whatever , and then plan a route.	QMSum_45

false

Yeah.

QMSum_51

false

Um then celebration.

QMSum_51

false

Celebration.

QMSum_51

false

Cel celebration yes , yes.

QMSum_51

false

Ah.

QMSum_51

false

Today we have apple juice and after we sell m million of 'em we have champagne.

QMSum_51

false

So I I thank you all very much. Um , I think this was very good and um

QMSum_51

false

Yeah.

QMSum_51

false

Mm-hmm.

QMSum_51

false

I think we did come up with a new product that's uh feasible. Feasible from the production point of view and feasible from a marketing point of view.

QMSum_51

false

Mm-hmm. Mm-hmm.

QMSum_51

false

So , thank you.

QMSum_51

false

Okay.

QMSum_51

false

Yeah.

QMSum_51

false

Thank you.

QMSum_51

false

Thank you very much.

QMSum_51

false

Okay. Watch I I have my cord behind you here.

QMSum_51

false

Okay.

QMSum_51

false

Okay.

QMSum_51

false

I always get it on here , but getting it off is

QMSum_51

false

Do we do we have some time left ? Uh you have

QMSum_51

false

They say it's forty minutes.

QMSum_51

false

Ah yes we have time later

QMSum_51

false

But we we were told we could end the final meeting at any time , whenever we felt we were finished.

QMSum_51

false

but we don't

QMSum_51

false

Okay.

QMSum_51

false

Oh , alright.

QMSum_51

false

It'll take me the rest of the time to get my microphone out from my necklace. Oh , there we go.

QMSum_51

false

Why ?

QMSum_45

false

Um.

QMSum_45

false

I 'm known. I

QMSum_45

false

No , cuz she already told me it , before she told you.

QMSum_45

false

No , she told me a long time ago. She told me she told me like two weeks ago.

QMSum_45

false

Oh , well , it doesn't matter what time.

QMSum_45

false

OK. You know how to toggle the display width function

QMSum_45

false

Well maybe she hadn't just started transcribing me yet.

QMSum_45

false

Wow.

QMSum_45

false

Anyway.

QMSum_45

false

What is it ?

QMSum_45

false

Let me explain something to you.

QMSum_45

false

Um ,

QMSum_45

false

My laugh is better than yours.

QMSum_45

false

there.

QMSum_45

false

I beg to differ.

QMSum_45

false

Yo.

QMSum_45

false

Um , OK.

QMSum_45

false

But you have to say something genuinely funny before you 'll get an example.

QMSum_45

false

Yeah.

QMSum_45

false

The thing is I don't know how to get to the next page. Here.

QMSum_45

false

No. You should be at least be self - satisfied enough to laugh at your own jokes.

QMSum_45

false

Actually I thought

QMSum_45

false

No , it 's a different laugh.

QMSum_45

false

There.

QMSum_45

false

Ooh , wow !

QMSum_45

false

How weird.

QMSum_45

false

Oh ! Holy mackerel.

QMSum_45

false

Wow. Whoa !

QMSum_45

false

What ? ! Oh. OK. I wasn't even doing anything. OK.

QMSum_45

false

Uh.

QMSum_45

false

Eva 's got a laptop , she 's trying to show it off.

QMSum_45

false

That was r actually Robert 's idea. But anyhow. Um

QMSum_45

false

O K. So , here we are.

QMSum_45

false

Once again.

QMSum_45

false

Once again , right , together. Um , so we haven't had a meeting for a while , and and probably won't have one next week , I think a number of people are gone. Um , so Robert , why don't you bring us up to date on where we are with EDU ?

QMSum_45

false

Um , uh in a in a smaller group we had uh , talked and decided about continuation of the data collection. So Fey 's time with us is almost officially over , and she brought us some thirty subjects and , t collected the data , and ten dialogues have been transcribed and can be looked at. If you 're interested in that , talk to me. Um , and we found another uh , cogsci student who 's interested in playing wizard for us. Here we 're gonna make it a little bit more complicated for the subjects , uh this round. She 's actually suggested to look um , at the psychology department students , because they have to partake in two experiments in order to fulfill some requirements. So they have to be subjected , before they can actually graduate. And um , we want to design it so that they really have to think about having some time , two days , for example , to plan certain things and figure out which can be done at what time , and , um , sort of package the whole thing in a in a re in a few more complicated um , structure. That 's for the data collection. As for SmartKom , I 'm the last SmartKom meeting I mentioned that we have some problems with the synthesis , which as of this morning should be resolved. And , so ,

QMSum_45

false

Good.

QMSum_45

false

" should be " means they aren't yet , but but I think I have the info now that I need. Plus , Johno and I are meeting tomorrow , so maybe uh uh , when tomorrow is over , we 're done. And ha n hav we 'll never have to look at it again Maybe it 'll take some more time , to be realistic , but at least we 're we 're seeing the end of the tunnel there. That was that. Um , the uh , uh I don't think we need to discuss the formalism that 'll be done officially s once we 're done. Um , something happened , in on Eva 's side with the PRM that we 're gonna look at today , and um , we have a visitor from Bruchsal from the International University. Andreas , I think you 've met everyone except Nancy.

QMSum_45

false

Sorry. Hi. Hi.

QMSum_45

false

Yeah.

QMSum_45

false

Hi. Hi.

QMSum_45

false

So when you said " Andreas " I thought you were talking about Stolcke.

QMSum_45

false

And , um ,

QMSum_45

false

Now I know that we aren't , OK.

QMSum_45

false

Andy , you actually go by Andy , right ? Oh , OK.

QMSum_45

false

Yeah.

QMSum_45

false

Eh

QMSum_45

false

Cuz there is another Andreas around ,

QMSum_45

true

Hmm.

QMSum_45

false

so , to avoid some confusion.

QMSum_45

false

That will be Reuter ? Oh , OK.

QMSum_45

false

Yeah.

QMSum_45

false

So my scientific director of the EML is also the dean of the International University , one of his many occupations that just contributes to the fact that he is very occupied. And , um , the um , he @ @ might tell us a little bit about what he 's actually doing , and why it is s somewhat related , and by uh using maybe some of the same technologies that we are using. And um. Was that enough of an update ?

QMSum_45

false

I think so.

QMSum_45

false

In what order shall we proceed ?

QMSum_45

false

OK.

QMSum_45

false

Maybe you have your on - line

QMSum_45

false

Uh , yeah , sure. Um , so , I 've be just been looking at , um , Ack ! What are you doing ? Yeah. OK. Um , I 've been looking at the PRM stuff. Um , so , this is , sort of like the latest thing I have on it , and I sorta constructed a couple of classes. Like , a user class , a site class , and and you know , a time , a route , and then and a query class. And I tried to simplify it down a little bit , so that I can actually um , look at it more. It 's the same paper that I gave to Jerry last time. Um , so basically I took out a lot of stuff , a lot of the decision nodes , and then tried to The red lines on the , um , graph are the um , relations between the different um , classes. Like , a user has like , a query , and then , also has , you know um , reference slots to its preferences , um , the special needs and , you know , money , and the user interest. And so this is more or less similar to the flat Bayes - net that I have , you know , with the input nodes and all that. And So I tried to construct the dependency models , and a lot of these stuff I got from the flat Bayes - net , and what they depend on , and it turns out , you know , the CPT 's are really big , if I do that , so I tried to see how I can do , um put in the computational nodes in between. And what that would look like in a PRM. And so I ended up making several classes Actually , you know , a class of with different attributes that are the intermediate nodes , and one of them is like , time affordability money affordability , site availability , and the travel compatibility. And so some of these classes are s some of these attributes only depend on stuff from , say , the user , or s f just from , I don't know , like the site. S like , um , these here , it 's only like , user , but , if you look at travel compatibility for each of these factors , you need to look at a pair of , you know , what the um , preference of the user is versus , you know , what type of an event it is , or you know , which form of transportation the user has and whether , you know , the onsite parking matters to the user , in that case. And that makes the scenario a little different in a PRM , because , um , then you have one - user objects and potentially you can have many different sites in in mind. And so for each of the site you 'll come up with this rating , of travel compatibility. And , they all depend on the same users , but different sites , and that makes a I 'm tr I w I wa have been trying to see whether the PRM would make it more efficient if we do inferencing like that. And so , I guess you end up having fewer number of nodes than in a flat Bayes - net , cuz otherwise you would c well , it 's probably the same. But um , No , you would definitely have be able to re - use , like , um , all the user stuff , and not not having to recompute a lot of the stuff , because it 's all from the user side. So if you changed sites , you you can , you know , save some work on that. But , you know , in the case where , it depends on both the user and the site , then I 'm still having a hard time trying to see how um , using the PRM will help. Um , so anyhow , using those intermediate nodes then , this this would be the class that represent the intermediate nodes. And that would basically it 's just another class in the model , with , you know , references to the user and the site and the time. And then , after you group them together this no the dependencies would of the queries would be reduced to this. And so , you know , it 's easier to specify the CPT and all. Um , so I think that 's about as far as I 've gone on the PRM stuff.

QMSum_45

false

Well

QMSum_45

false

Right.

QMSum_45

false

No. So y you didn't yet tell us what the output is.

QMSum_45

false

The output.

QMSum_45

false

So what decisions does this make ?

QMSum_45

false

OK. So it only makes two decisions , in this model. And one is basically how desirable a site is meaning , um , how good it matches the needs of a user. And the other is the mode of the visit , whether th It 's the EVA decision. Um , so , instead of um , doing a lot of , you know , computation about , you know , which one site it wants of the user wants to visit , I 'll come well , try to come up with like , sort of a list of sites. And for each site , you know , where h how how well it fits , and basically a rating of how well it fits and what to do with it. So. Anything else I missed ?

QMSum_45

false

So that was pretty quick. She 's ac uh uh Eva 's got a little write - up on it that uh , probably gives the the details to anybody who needs them. Um , so the You you didn't look at all yet to see if there 's anybody has a implementation.

QMSum_45

false

No , not yet , um

QMSum_45

false

OK. So one so one of the questions , you know , about these P R Ms is

QMSum_45

false

Mm - hmm.

QMSum_45

false

uh , we aren't gonna build our own interpreter , so if if we can't find one , then we uh , go off and do something else and wait until s one appears. Uh , so one of the things that Eva 's gonna do over the next few weeks is see if we can track that down. Uh , the people at Stanford write papers as if they had one , but , um , we 'll see. So w Anyway. So that 's a a major open issue. If there is an interpreter , it looks like you know , what Eva 's got should run and we should be able to actually um , try to solve , you know , the problems , to actually take the data , and do it. Uh , and we 'll see. Uh , I actually think it is cleaner , and the ability to instantiate , you know , instance of people and sites and stuff , um , will help in the expression. Whether the inference gets any faster or not I don't know. Uh , it wouldn't surprise me if it if it doesn't.

QMSum_45

false

Mm - hmm.

QMSum_45

false

You know , it 's the same kind of information. I think there are things that you can express this way which you can't express in a normal belief - net , uh , without going to some incredible hacking of sort of rebuilding it on the fly. I mean , the notion of instantiating your el elements from the ontology and stuff fits this very nicely and doesn't fit very well into the extended belief - net. So that was one of the main reasons for doing it. Um. I don't know. So , uh , people who have thought about the problem , like Robert i it looked to me like if Eva were able to come up with a you know , value for each of a number of uh , sites plus its EVA thing , that a travel planner should be able to take it from there. And you know , with some other information about how much time the person has and whatever , and then plan a route.

QMSum_45