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GoDiS and TrindiKit MITRE workshop 27/10-03. Staffan Larsson Göteborg University Sweden. TrindiKit and GoDiS. TrindiKit Toolkit for building and experimenting with dialogue move engines (dialogue managers) Information state update approach Information states Update rules Dialogue moves

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trindikit and godis
Goteborg University Dialogue Systems LabTrindiKit and GoDiS
  • TrindiKit
    • Toolkit for building and experimenting with dialogue move engines (dialogue managers)
    • Information state update approach
      • Information states
      • Update rules
      • Dialogue moves
  • GoDiS
    • A dialogue system implemented with TrindiKit
    • Issue-based dialogue management
    • Versions for Inquiry (IOD) and Action-oriented dialogue (AOD) genres
dialogue task and source of back end information
Goteborg University Dialogue Systems LabDialogue task and source of back-end information
  • Task
    • Medical diagnosis
    • Information about diseases
  • Source of back-end information
    • Java backend application
    • Conntected to GoDiS using OAA
    • Not just a database
      • Also provides which questions to ask and which tests to perform
      • Dynamic dialogue planning
  • Type of dialogue
    • Inquiry-oriented
    • System-driven dialogue
    • Single task (but more can be added)
slide4
Goteborg University Dialogue Systems Lab

control

DME

input

inter-

pret

update

select

gene-

rate

output

  • TIS
  • DEVICES LEXICON DOMAIN

backend

interface

lexicon

domain

knowledge

modules we needed to change for this exercise
Goteborg University Dialogue Systems LabModules we needed to change for this exercise
  • Resources
    • Domain knowledge resource
      • Dialogue plans
      • Ontology
    • Device interface
      • Connection to Java database via OAA
    • Lexicon
      • Includes synonyms, extracted from backend
  • Modules
    • Some minor bug-fixes and improvements
    • These are not domain-specific, and will thus be reused in other domains
domain knowledge
Goteborg University Dialogue Systems LabDomain knowledge
  • Dialogue plans for dealing with diagnosis
    • ?x.disease(x): ”which disease is diagnosed?”
    • ?confirmed_by_interview: ”Is the diagnosis confirmed by additional information?”
    • ?confirmed_by_tests: ”Is the diagnosis confirmed by medical tests?”
  • These issues are all assumed to be open when dialogue starts
  • Additional plans
    • ?x.info(x): ”What information is there about a given disease?”
    • ?x.treatment(x): ”What treatment is there for a given disease?”
alternate solutions
Goteborg University Dialogue Systems LabAlternate solutions
  • User-driven dialogue
    • Not load issues when resetting; user has to raise all issues
    • Usr can ask sys to
      • Provide a diagnosis
      • Confirm whether usr has give disease
  • Decision trees as dialogue plans
    • Move backend knowledge into dialogue plans
    • Information conversion could be done automatically
  • Separate genre: expert system dialogue
    • Add special purpose update rules
    • Dynamic dialogue planning by expert
what was added to godis
Goteborg University Dialogue Systems LabWhat was added to GoDiS?
  • 2 update rules
    • exec_assume
      • If assume(P) on top of plan, add P to /SHARED/COM
    • exec_assume_issue
      • If assume_issue(Q) on top of plan, push Q on SHARED/ISSUES
  • Possible useful additions
    • Subplans
    • Precedence constraints on tasks
highlights
Goteborg University Dialogue Systems LabHighlights
  • Reuse of GoDiS -> you get for free:
    • Feedback, grounding, sequencing
      • Though this is more useful with speech
    • Accommodation and clarification
      • incl. simple plan recognition (dependent issues)
    • Multiple simultaneous issues & information sharing between plans
  • High level of abstraction in dialogue plans
  • Modularity -> rapid prototyping
  • Separation of lexicon from domain knowledge
    • Additional languages can be easily added, and language can be changed online
lowlights
Goteborg University Dialogue Systems LabLowlights
  • GoDiS has not been used for this type of application, so not completely straightforward
    • Backend, not dialogue plans, determines which question should be asked next
    • Solution: each plan is loaded several times, until goal issue has been resolved
  • Generation and interpretation a bit tacky
  • Had to use AOD version to connect to device
    • Need to make an IOD version for devices
  • Accommodation has to be helped with ”bind”
    • Suggests different datastructure for plans
accommodation and clarification
Goteborg University Dialogue Systems LabAccommodation and clarification

S> Are you feeling nauseous?

U> yes and i have a headache [score 0.0-1.0]:0.8

S> Okay. headache.

U> yes

S> Hello

U> malaria

S> malaria. I dont quite understand. Do you want to confirm by interview , to confirm by taking tests , to get general information or to ask about treatment?

tested with real users
Goteborg University Dialogue Systems LabTested with real users?
  • So far, not much
    • A little bit done by students
  • Starting soon (before Xmas)
    • Corpus collection
    • Application: VCR programming
multiple simultaneous issues information sharing
Goteborg University Dialogue Systems LabMultiple simultaneous issues, information sharing

S> Hello How are you feeling today?

U> I have a headache

S> Okay. Are you feeling nauseous?

U> Um… can I have som information about a disease?

S> Okay. Lets see. What disease do you want to know about??

U> I also want to know about treatment

S> Okay. Lets see. What disease do you want to know about??

U> malaria

S> Malaria can be cured with prescription drugs…

S> Returning to the issue of information. Malaria is a serious, sometimes fatal, disease caused by a parasite…

S> Returning to the issue of your diagnosis. Are you feeling nauseous?

godis aod information state
Goteborg University Dialogue Systems LabGoDiS-AOD information state

AGENDA : stack( Action )

PLAN : stackset( Action )

PRIVATE :

BEL : set( Prop )

TMP : (same type as SHARED)

COM : set( Prop )

ACTIONS : stackset( Action )

SHARED :

QUD : stackset( Question )

ISSUES: stackset(Question)

LU:…

how to use trindikit
How to use TrindiKit

We start from TrindiKit

Implements the information state approach

Takes care of low-level programming: dataflow, datastructures etc.

Goteborg University Dialogue Systems Lab

TrindiKit

information state

approach

how to build a basic system
How to build a basic system

Formulate a basic dialogue theory

Information state

Dialogue moves

Update rules

Add appropriate modules (speech recognition etc)

Goteborg University Dialogue Systems Lab

basic

dialoguetheory

basic system

TrindiKit

information state

approach

how to build a genre specific system
How to build a genre-specific system

Add genre-dependent IS components, moves and rules

Goteborg University Dialogue Systems Lab

genre-specific theory

additions

genre-specific system

basic

dialoguetheory

basic system

TrindiKit

information state

approach

how to build an application
How to build an application

Add application-specific resources

Goteborg University Dialogue Systems Lab

application

domain & language

resources

genre-specific theory

additions

genre-specific system

basic

dialoguetheory

basic system

TrindiKit

information state

approach

slide21
Goteborg University Dialogue Systems Lab

application-specific

Xerox

manual

home

device

manager

Travel

Agency

VCR

manager

Auto-

route

genre-specific

GoDiS-I

GoDiS-A

IBDM

GoDiS

TrindiKit

IS

approach

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