Datasets:

elplaguister

/

DTS_line_datasets

like 0

That 's really neat.

QMSum_87

Yeah.

QMSum_87

Yeah , there 's a lot of backchannel , a lot o a lot of

QMSum_87

This is really interesting data.

QMSum_87

Yeah , it is.

QMSum_87

I think what 's really interesting though , it is before d saying " yes , meetings have a lot of overlaps " is to actually find out how many more we have than two - party.

QMSum_87

I think so too , I think

QMSum_87

Cuz in two - party conversations , like Switchboard , there 's an awful lot too if you just look at backchannels , if you consider those overlaps ? it 's also ver it 's huge. It 's just that people haven't been looking at that because they 've been doing single - channel processing for speech recognition.

QMSum_87

Mm - hmm.

QMSum_87

Mm - hmm ?

QMSum_87

So , the question is , you know , how many more overlaps do you have of , say the two - person type , by adding more people. to a meeting , and it may be a lot more but i it may it may not be.

QMSum_87

Well , but see , I find it interesting even if it wasn't any more ,

QMSum_87

So.

QMSum_87

because since we were dealing with this full duplex sort of thing in Switchboard where it was just all separated out we just everything was just nice ,

QMSum_87

Mm - hmm ?

QMSum_87

so that so the issue is in in a situation where th that 's

QMSum_87

Well , it 's not really " nice ". It depends what you 're doing. So if you were actually having , uh depends what you 're doing , if Right now we 're do we have individual mikes on the people in this meeting. So the question is , you know " are there really more overlaps happening than there would be in a two - person party ".

QMSum_87

Mm - hmm ?

QMSum_87

And and there well may be , but

QMSum_87

Let let m let me rephrase what I 'm saying cuz I don't think I 'm getting it across. What what I what I shouldn't use words like " nice " because maybe that 's too i too imprecise. But what I mean is that , um in Switchboard , despite the many many other problems that we have , one problem that we 're not considering is overlap. And what we 're doing now is , aside from the many other differences in the task , we are considering overlap and one of the reasons that we 're considering it , you know , one of them not all of them , one of them is that w uh at least , you know I 'm very interested in the scenario in which , uh both people talking are pretty much equally audible , and from a single microphone. And so , in that case , it does get mixed in , and it 's pretty hard to jus to just ignore it , to just do processing on one and not on the other.

QMSum_87

I I agree that it 's an issue here but it 's also an issue for Switchboard and if you think of meetings being recorded over the telephone , which I think , you know , this whole point of studying meetings isn't just to have people in a room but to also have meetings over different phone lines.

QMSum_87

Mm - hmm.

QMSum_87

Maybe far field mike people wouldn't be interested in that but all the dialogue issues still apply ,

QMSum_87

Mm - hmm.

QMSum_87

so if each of us was calling and having a meeting that way you kn you know like a conference call. And , just the question is , y you know , in Switchboard you would think that 's the simplest case of a meeting of more than one person ,

QMSum_87

Mm - hmm.

QMSum_87

and I 'm wondering how much more overlap of the types that that Jane described happen with more people present. So it may be that having three people is very different from having two people or it may not be.

QMSum_87

That 's an important question to ask.

QMSum_87

So.

QMSum_87

I think what I 'm All I 'm s really saying is that I don't think we were considering that in Switchboard.

QMSum_87

Not you , me. But uh but but

QMSum_87

Were you ?

QMSum_87

Though it wasn't in the design.

QMSum_87

Were you were you were you were you measuring it ? I mean , w w were

QMSum_87

There there 's actually to tell you the truth , the reason why it 's hard to measure is because of so , from the point of view of studying dialogue , I mean , which Dan Jurafsky and Andreas and I had some projects on , you want to know the sequence of turns.

QMSum_87

Yeah.

QMSum_87

So what happens is if you 're talking and I have a backchannel in the middle of your turn , and then you keep going what it looks like in a dialogue model is your turn and then my backchannel ,

QMSum_87

Yeah.

QMSum_87

even though my backchannel occurred completely inside your turn.

QMSum_87

Yeah ?

QMSum_87

So , for things like language modeling or dialogue modeling it 's We know that that 's wrong in real time.

QMSum_87

Yeah ?

QMSum_87

But , because of the acoustic segmentations that were done and the fact that some of the acoustic data in Switchboard were missing , people couldn't study it , but that doesn't mean in the real world that people don't talk that way. So , it 's um

QMSum_87

Yeah , I wasn't saying that. Right ? I was just saying that w now we 're looking at it.

QMSum_87

Well , we 've als

QMSum_87

And and and , you you maybe wanted to look at it before but , for these various technical reasons in terms of how the data was you weren't.

QMSum_87

Right. We 're looking at it here.

QMSum_87

So that 's why it 's coming to us as new even though it may well be you know , if your if your hypothes The hypothesis you were offering eh

QMSum_87

Um.

QMSum_87

Right ? if it 's the null poth hypothesis , and if actually you have as much overlap in a two - person , we don't know the answer to that. The reason we don't know the answer to is cuz it wasn't studied and it wasn't studied because it wasn't set up. Right ?

QMSum_87

Yeah , all I meant is that if you 're asking the question from the point of view of what 's different about a meeting , studying meetings of , say , more than two people versus what kinds of questions you could ask with a two - person meeting.

QMSum_87

Mm - hmm ?

QMSum_87

It 's important to distinguish that , you know , this project is getting a lot of overlap but other projects were too , but we just couldn't study them. And and so uh

QMSum_87

May have been. May have been. Right ?

QMSum_87

Well , there is a high rate ,

QMSum_87

We do kn we don't know the numbers.

QMSum_87

So. It 's but I don't know how high , in fact

QMSum_87

Well , here I have a question.

QMSum_87

that would be interesting to know.

QMSum_87

See , I mean , i i le let me t I mean , my point was just if you wanted to say to somebody , " what have we learned about overlaps here ? " just never mind comparison with something else ,

QMSum_87

Mm - hmm.

QMSum_87

what we 've learned about is overlaps in this situation , is that the first the first - order thing I would say is that there 's a lot of them. Right ?

QMSum_87

Yeah.

QMSum_87

In in the sense that i if you said if i i i

QMSum_87

Yeah , I I don't di I agree with that.

QMSum_87

In a way , I guess what I 'm comparing to is more the common sense notion of how how much people overlap. Uh you know the fact that when when when , uh , Adam was looking for a stretch of of speech before , that didn't have any overlaps , and he w he was having such a hard time and now I look at this and I go , " well , I can see why he was having such a hard time ".

QMSum_87

Right. That 's also true of Switchboard.

QMSum_87

It 's happening a lot.

QMSum_87

It may not be

QMSum_87

I wasn't saying it wasn't.

QMSum_87

Right. So it 's just , um

QMSum_87

Right ? I was commenting about this.

QMSum_87

OK. All I 'm saying is that from the

QMSum_87

I 'm saying if I I 'm saying if I have this complicated thing in front of me , and we sh which , you know we 're gonna get much more sophisticated about when we get lots more data , But Then , if I was gonna describe to somebody what did you learn right here , about , you know , the the modest amount of data that was analyzed I 'd say , " Well , the first - order thing was there was a lot of overlaps ". In fact and it 's not just an overlap bunch of overlaps second - order thing is it 's not just a bunch of overlaps in one particular point , but that there 's overlaps , uh throughout the thing.

QMSum_87

Right.

QMSum_87

Right. No , I I agree with that.

QMSum_87

And that 's interesting. That 's all.

QMSum_87

I 'm just saying that it may the reason you get overlaps may or may not be due to sort of the number of people in the meeting.

QMSum_87

Oh yeah.

QMSum_87

And that 's all.

QMSum_87

Yeah. Yeah , I wasn't making any statement about that.

QMSum_87

And and it would actually be interesting to find out

QMSum_87

Yeah.

QMSum_87

because some of the data say Switchboard , which isn't exactly the same kind of context , I mean these are two people who don't know each other and so forth , But we should still be able to somehow say what what is the added contra contribution to sort of overlap time of each additional person , or something like that.

QMSum_87

Yep.

QMSum_87

Yeah , that would be good to know ,

QMSum_87

What

QMSum_87

but w we

QMSum_87

OK , now.

QMSum_87

I could certainly see it going either way.

QMSum_87

Wh - yeah , I I agree I agree with Adam.

QMSum_87

But yeah.

QMSum_87

Yeah.

QMSum_87

And the reason is because I think there 's a limit there 's an upper bound on how many you can have , simply from the standpoint of audibility. When we speak we we do make a judgment of " can " you know , as adults.

QMSum_87

Right.

QMSum_87

Mm - hmm.

QMSum_87

I mean , children don't adjust so well , I mean , if a truck goes rolling past , adults will well , depending , but mostly , adults will will will hold off to what to finish the end of the sentence till the till the noise is past.

QMSum_87

Mm - hmm.

QMSum_87

And I think we generally do monitor things like that , about whether we whether our utterance will be in the clear or not.

QMSum_87

Right.

QMSum_87