re

okay like to welcome everybody see this

a special session a natural language generation for dialogue systems

i'm just gonna give a five minute overview of the session then we'll have a

couple of long talks accomplish very short talks and then we'll have a panel

and

about a lot of this kind of came together to organize this so the other

organisers of their temper like a kind reader david how corrupt

showing or read and very in a research

so the

what the organizers task is to do is to say like why we would have

a special

session on a nlg for dialogue systems

and you know because you might think well this

areas been around for a long time indeed some of the earliest work

on computational models for natural language generation was work done in the context of a

dialogue system or question answering system like kathy make humans

early work for phil collins early work

there's also a lot of earlier much earlier work you note going back almost twenty

years

people doing starting to do statistical

work on statistical natural language

generation

starting with the kind of seminal work of like alien like who showed that you

could kind of have a very loosely configured hybrid

linguistic statistical representation where you could overgenerate and then you could learn

rightly rules and filter out

this filter out the data's you could produce and so that works as old as

nineteen ninety eight so you might

still say like why would you have the special session now and also in the

context of darpa communicator conversational dialogue systems

i edited a special issue with computers

speech and language are not sure language generation for spoken dialogue

and the number of people that you know had papers in the special issue including

am and i lasso and ridge alex rudnicky mari ostendorf stephanie seneff so a lot

of long time people been working on conversational dialogue systems

for years

but the reason that we wanted to have this special session despite the fact that

these a lot of that

its of generation for dialogue have been around a long time is that there's been

a recent kind of resurgence of interest in a natural language generation because of kind

of the

ai renaissance i guess we should say all the interest in chat bots and all

the consumer products that are out there now like collects and google system

the other thing is that the availability of large online corpora like open subtitles or

twitter or

i you know corpora like that have led have may people wonder whether they could

actually use a purely

statistical kind of and machine translation approach to produce dialogue turns in an open-domain way

so there's been a lot of activity in that area for the last five years

and

so

so there's a lot you know seems to be a lot of different stuff going

on of this field and one of the reasons why i wanted to organize the

special session was the kind of

be able to look at what we can do now with different generation techniques into

bring you know

it especially in the panel to bring in a panel of experts people who worked

on one language generation for dialogue systems and try to get some different perspectives

on from

from their from their points of view what kinds of techniques which ones don't work

which things the ready for primetime it could go into consumer products in which things

are still just

kind of basic

research ideas

and when am i am particular interest and i think that of many of the

other people to organize the panel who have put out these other challenges but e

two e challenge is also the web nlg challenge now is in interest and stylistic

variation in some of the classic things the natural language generation sabine able to do

in their sentence planner and like and a kind of interest in whether

and to and framework is actually without a lot of extra architectural details that kind

of model the traditional natural language

architecture whether they're actually gonna be able to produce different kinds of

stylistic variation like the

previous generation of statistical language generations could do

so that's kind of why were here

and

we have

too long papers

redundancy localisation for the conversation of unstructured responses and that a neural language generation in

dialogue paper

we have to short papers that will be presented in five minutes the for the

panel

and they'll be in the poster session later i wanted to have them in

in the discussion in our in our minds before we start doing the panel

because i think

there's a really interesting thing here of a new generation challenge that aims to be

a little bit more complicated than what people then you seen in the neural generation

framework

and then somebody was really

hot of the starting box

and that

the corpus was released in two weeks later they had a they this

character the character out of the box model that uses the corpus of this is

all kind of very much

breaking news

and

so we can go ahead and

get started for the for the main papers and then we'll have the panel at

the

at the end

okay so sebastian