and thirty one

i

i'm happy lasttime applied is due to indicate that at university

and

and today representing a study on are self disclosure in conversation dialogue system

so i haven't recovers also if you can't understand i'm happy i said

so this was the study was done as part of the cmu my is the

i v and is not exactly in two thousand seven

well as in just standing there is close to

so it's because human conversations of in humans and y are many solutions to think

is right here try to achieve the solution and restart it can be in of

all those that so propositional function based

i have any information of the conversation those that so interactional con functions with just

a system like the quantization for one

and so in cost functions which is

trying to build that of the essential between those who participated

so set motion is one of the key social strategy employed in conversation and intimacy

between pocketsphinx and interleaved idea of the conversation

so many definitions on the one wants to self disclosure

i o one is that strong or mean and it in nineteen seventy three which

defined as the one a static

all opinions or but experiences references by you and wasn't it

so

so

a no side distortion is a very interesting phenomenon in between very well studied by

the psychology community

in particular because of

it's actually the ability to use reciprocity and dyadic interaction

so that you must leave the phenomenon vibrates when one participated in a conversation self

disclosure

the other participants in most competitive set of discourse in this form

and there are many explanations on this but the exact called also based on the

screen on that's not what is the one hypothesis is that it's a formal solution

extreme where the party receiving side distortions this feels obligated but also said this goal

i don't know what concerns is that it's a solution conversational where if a

it doesn't sound is close and return they feel uncomfortable

and i and hypothesis is about social just attraction

ones that is close to people and that's close to that of because i

as i do not trust in like a by the exact it's not what a

distance between a pretty well established a

and right of self disclosure and have been reproduced in many studies and shall

to be a very strong

so subsequent studies also show other ask exercise caution like

a self disclosure reciprocity characterizes initial social interaction because people set is closely to try

to corpsman model

i interestingly you look at a distance to be high school

and actually to be better eliciting self disclosure

also is not it your relationship between this process and it

so it's not expected that a higher amount of self disclosure that make someone like

you

so

that's has been studied for a conversation between human

but really interested to know if the same it's that is close to have the

thing i think in human machine i work

and if it does

that would have

implications for systems which came to elicit information from the user point o to maybe

also more pleasant nice experiences all the methods you task completion

but the key axes

two months that machines don't have sort since you things of that one so any

set this can also apply machine guns that is coming across as dishonest

by the starting point is that night maybe force that humans actually something you computers

a solution that so almost macabre thinking about n i the second source you to

stick study was split

in human conversation the human machine and or

okay so i'm

we are talking now about the context in which we can you contacted is that

so everyone who works in dialogue was how difficult it is together data

but

exactly in two thousand seven amazon had an example right channel

we had a noun in some university students to was channel one on amazon devices

and so this was a pretty one because

we actually get that uses the real world instead of

you know i think something expensive test it

so you want one of sixteen dialogue instance that hosted on the alex at the

right

at this could be able to use the united states of the command that's chat

and you that's what i didn't the data and it is seen that i don't

issues so they didn't know which of the dialog state tracking with

so

it looks like interesting because

i think it was that's what she to end the conversation at any time so

a data and happens

you domain so please specify started goals

so the only reason that even continue the conversation was for that when entertainment

so at the end of the conversation user is allowed only at the interaction the

scale of one point five based on the that they would interact with the social

want to get it also three shows more anybody

so three hundred and nineteen out of the fifteen or one thousand five hundred users

decided to anybody

and well known talking about the dialogue agent that we had in the next upgrade

so that i don't agent was based on a finite state machine architecture and what

this means that every step was a of the finite state machine

with essentially the response that we wanted to give as a dialogue system

and transitions what condition don't use the sentiment

so just an example of how this might look

so madness aside dialogue it and it's the entire house and green

in the users say something more stable be reports to like not but not by

then minus encyclopedia anything special happen if response posted but in the user to say

something that sounds naked

in tries to get a sympathetic response adidas them what's wrong so in this way

we had essentially the order of topics of the conversation

so maybe firstly the user then

acknowledge the positive or negative response then you try to talk about the initial

where we asked if they are interested in one of the latest tv shows if

they said that they are not interested that we asked them about a nice in

the if they say they were not interest in the movie i don't want game

in this example intuition that we show the movie we did spend some time chatting

about that it is that it is that you see you with the

then eventually all users what invited to leon you believe that out just choose not

appeared again and again what kind of one of these long winded word idioms and

they could also choose to exhibit limit in there

now a deterministic which was right

i don't need to impose taking initiative but al

all from the stage one with a conversation initiator shifted to the user

and they could talk to a dialog agent about anything and we try to get

responses from

other sources from the way

so on is

about i dialogue into

but the specifying chat bots that we used in this study would integer different so

we randomly assigned the users who interacted with the system

one of two chat bots or one of them i think in c is a

very high self disclosing chat board from the beginning of the conversation

so in that uses when the machine that's how's it going in the user sees

not i'm not the channel response with the story about itself with this kind of

your because

that's it is directly related to there's been chilling a to b and catching up

with my friends they just got them and whatever you an expression that they shouldn't

one

and the machine i mean of the dialog agent does not really had a frame

is often to work about it

but

then the humans experiment to see a play today i quite enjoyed

by a group of humans

the see a dialog agent that did not end of story about itself it is

c is all that's create anything a specialization towards technology and is the next question

so now on this was the setting under which we

and i'm not experiment

but not only interested in identifying when you with the we use i with exactly

that are dialog data

actually said is close and stick with defining all what we consider the self disclosure

so in the context of conversations with a dialog agent we said that self disclosure

has to be wanted at and it should be information di otherwise the dialogue agent

should market

so this does not include non-systematic questions for example so in the example given

so if you see when a system see what we collected anything special

and the use this is nothing that changes going on physically with my notes today

so that what constitutes a disclosure

but what exactly fifty times in the movie a time to learn the user sees

i need identity of a bit bigger block on dataset disclosure because it is adjusted

it it's possible question and that you have any extra information

so in this paper a three hundred and nineteen conversations were labeled for a user

self disclosure

and we manage to get a substantial agreement on there

by

we actually had a much larger corpus of conversations which it was not possible

human annotators to allocate every user utterance for self disclosure

so what we do this we built an svm classifier

are trained on this corpus to be able to the entire corpus for all occurrences

of the service goes

so this is the things just is designed to say one going to justify

but the classifier or a accuracy of ninety one point seven percent and or

f one score of sixty seven percent so it was fairly a little bit

okay so now we had

the user utterances which

one instances of self disclosure because we got a classifier to label the whole corpus

i mean or when a machine is close because we designed this is so now

that's allowed us to study the effects of status close to

so are the first one if you want to start with lexical

so

what we did this we studied

in how many users are disclosed and done before to sell disclosing user utterance

is the of the machines at school and we note that users was significantly more

likely to set the schools following of machine that the solution

then when a machine didn't set is close

you know at a door immediately following the for instance of machine self disclosure

and we found its users were much more likely to set it is close even

at the beginning of the quantization of the o

matching after a system set is close

so we set our study other question

the project and a conversations but initial user self disclosure actually longer

an internal yes there were a they were significantly lower

we also want to study if you that's what is close initially do they disclose

of the conversation and i don't know that if someone doesn't so close initially

much less likely to sell it is close to the correlation

so

i don't know question we started was a user will choose not to sell disclose

initially estimated as in just employing machine interest and this is kinda based on the

motion of people having no god it was not

so the way we tested this was a bit a reference to i would do

so we are able to set was initially one more likely to fail to one

and only if they do play the work in for how long deeply working

so yes a the users who a source not a set of is close initially

what actually much less likely to pay to what they also if needed in the

volume deflated what a much shorter time than

a user's we chose to say it's close

next we test the effect is close right in the likability in human

machine interaction

so since avalon provided us with sleeping of well with the people for a given

by the system again we use it as a proxy for online okay

and we thought we had a conversations make you would sell disclosed a lot i

mean the delayed of what vector

and

the and that is we don't know

so we wouldn't really find any correlation between over the user ratings and the a

mole this to disclose in the conversation then and we couldn't find a difference in

the ratings of the statistic located at what's as both within

and he couldn't find a difference in the ratings for conversations which have high service

also insist on with patients with discourse

and so it and a few movies

by we study the effect of set is close in a real-time that skin spoken

dialogue system give model being users in the real world of amazon alex that thanks

to a amazon

and what we found is that indicators of reciprocity have been even in human machine

quantization

and that

by the way how with are authentic as close as efficiently we can characterize the

behavior while the quantization

well what we also identified anything at relationship between san exclusion and like

thank you

first

the question so it's jules so well they're not aspects to self disclosure to adapt

of self disclosure elements of self disclosure and the study considers the only by at

o

future work would be to do this i'll probably but to do both positive and

negative as well or two of the data but the on sentence that i don't

more better we would find or relationship between self disclosure and liking

because i even in psychology it's not remote that

so that was the study in nineteen seventy three i think about what cost

would say that

so he divide itself is closer to three categories do medium and high essentially

and he found that and one set is closer to result in collecting but i

said distortion actually resulted in this and i think

and the reason is that i don't trust

people who say disclose very high

so that maybe

and interesting finding

was

i even like you an extra a i think that someone we gotta because they

have a block so well

i don't know anything that alex is hopelessly but an x and you might be

ignored

but they are this also five shows that people will be back to what we

so that also are similar

and are most of all black students were actually

the titanium believable that the machine could have anything like but

no effect on very clear people responded that wants to that's the

the actually believe that the machine thing

so we don't have instances of battery hundreds of people

what we did not particularly if they were different from the a believable back to

you

really of the reciprocity affect and reciprocity effects or and we would like to these

will store

first

so great question initially our work but only the shaded up to the

and we didn't really ask questions but then people never school us because they just

i know what to talk about rip of order

the initiative to do this architecture may be kept asking questions and we might get

one and i started do not include a direct responses to question

so even something like are not clearly a i even things like i did see

the movie we don't count those that self disclosure available they technically are giving information

because they're

just on sorting the question but the bare minimum of what require

so we only consider things with a probation it wasn't necessary as a as close

to

and that of the data collection

last

do you mean that is us

i think there had so the people are currently work

okay

okay i think