Dialog Models 11-716 September 18, 2003 Thomas Harris What is a - - PowerPoint PPT Presentation

Dialog Models

11-716 September 18, 2003 Thomas Harris

What is a (dialog) model?

• A model is an abstraction of a thing,

dimensionally reduced, while still informative of the thing with respect to a particular perspective.

• A dialog model is a process calculus of a

dialog, dimensionally reduced, while still informative of the dialog with respect to usability.

Why model?

• Not a good question. We always abstract,

hence we always model. Ask instead, “Why this model?”

• Grosz and Sidner ’86 – the deep end of

linguistics.

• TRINDI ’00ish – a modern survey.

Attentions, Intentions, and the Structure of Discourse

Barbara J. Grosz and Candance L. Sidner

Computational Linguistics, vol. 12, num 3, July-September 1986

11-716 Ariadna Font Llitjos September 25, 2001

New Theory of discourse structure

• As opposed to meaning (needs to partially rest on

the discourse structure)

• Stresses discourse purpose and processing
• 3 separate but interrelated components (needed to

explain interruptions, referring expressions, etc.):

– Linguistic structure (sequence of utterances) – Intentional structure – Attentional state

• This distinction simplifies both the

explanations given + computation mechanism used

• Speaker/hearer

ICP/OCP

Linguistic structure

• Utterances in a discourse are naturally aggregated

into discourse segments (like words into constituent phrases)

• Segments are not necessarily continuous

(interruptions)

• LS is not strictly decompositional
• 2-way interaction between discourse segment

structure and utterances constituting the discourse:

– linguistic expressions can convey info about discourse structure (cue phrases, ling. boundary markers) – Discourse structure constraints the interpretation of these ling. expressions

Intentional Structure

• Discourse (participants) have an overall purpose
• Even though there might be more than one, G&S

distinguish one as foundational to the discourse (vs. private purposes) which needs to be recognized

• Each discourse segment has a discourse segment

purpose (DSP), which contributes to the overall DP

Intentional structure cntd.

• 2 structural relationships between DSP:

– Dominance

DSP1 contributes to DSP2 = DSP2 dominates (DOM) DSP1

– Satisfaction-precedence (Parsing: linear precedence)

DSP1 satisfaction-precedes DSP2 when 1 must be satisfied before 2

• The dominance relation invokes a partial ordering
• n DSPs, i.e. a dominance hierarchy
• Determinations (complete specification of what is

intended by whom) vs. recognition

Attentional State

• As opposed to cognitive state, which is a richer

structure that includes knowledge, beliefs, desires and intentions

• Abstraction of the participants’ focus of

attention as their discourse unfolds (a property of the discourse itself)

• Dynamic: records the objects, properties and

relations that are salient at each point in the discourse

Attentional State cntd.

• Modeled by a set of focus spaces which constitute

the focusing structure

• A focus space = segment + DSP
• Although each focus space contains a DSP, the

focus structure does not include the intentional structure as a whole

• The stacking of focus spaces reflects the salience
• f entities in each space during the corresponding

segments of the discourse

Attentional State cntd.

• Focusing structure depends on the intentional

structure: the relationships between DSPs determine pushes and pops from the stack

• Focusing structure coordinates the linguistic and

intentional structures during processing (p. 181)

• Like the other 2 structure, focusing structure

evolves as discourse proceeds

Discourse examples

• Essay (p. 183)
• Task-oriented dialog (p. 186)

– Intentional structure is neither identical nor isomorphic to the general plan

Processing issues

• Intention recognition

– What info can the OCP use to recognize an intention – At what point does this info become available

• Overall processing module has to be able to
• perate on partial information
• It must allow for incrementally constraining the

range of possibilities on the basis of new info that becomes available as the segment progresses

• Info constraining DSP:

– Specific linguistic markers – Utterance-level intentions (Grice’s maxims) – General knowledge about actions and objects in the domain of discourse

• Applications of the theory:

– Interruptions (weak vs. strong) (p. 192) – Cue words (p. 196)

Properties and problems of discourse-level intentions

• DP/DSP are natural extensions of Grice’s

utterance-level meanings… but G&S don’t address meaning

• Remains to be seen whether x and f are equivalent

to DS and their features (p. 199)

• G&S state that the modes of correlation that
• perate at the utterance-level (c) also function at

the discourse level

Basic Generalization

• Discourse sufficiency: the intentional

structure need not be complete

• Belief case
• Action case

Conclusions

• Theory presented by G&S is a

generalization of theories of task-oriented dialogs, but it’s domain independent

• Interesting and thorough but infeasible

More conclusions

• Asks more questions than it answers.
• How do we implement these aspects of

dialog?

• Basically correct.

TRINDI

• circa 1998-2000
• European Community sponsored
• Göteborg , Edinburgh , Saarbrücken , SRI,

Cambridge , Xerox Research Centre Europe

• Effort to experiment and evaluate different

theoretical dialog models in a real system

Basic Toolkit Architecture

• Informational Components
• Formal Representations
• Dialog Moves
• Update Rules
• Control Strategy

Informational Components

• Data
• Participants
• Beliefs
• Common ground
• Intentions

Formal Representations

• Formal representation of informational

components

• Typed feature structures
• Lists
• Sets
• Propositions
• First order logic

Dialog Moves

• Trigger the update of the information

state

• Grammatical triggers
• External events

Update Rules

• Govern information state updates
• Sometimes incorporates domain knowledge
• Sometimes govern behavior of dialog

moves

Control Strategy

• Decide which update rule applies
• Simple priority list
• Game theory
• Utility theory
• Statistical methods

Dialog Theories

• Finite State Dialog Models
• Plan-based Models

Finite State Dialog Models

• Information is a state in the FSM
• Dialog moves are inputs matching

transitions

• Update Rules are FSM lookups and

transitions

• Control Strategy is static, the FSM itself

Plan-based Models

• Information state is the modeled beliefs,

desires, and intentions of the participants

• Dialog moves are speech acts, e.g. request

and inform

• Update rules are cognitive rules of evidence
• Control Strategies are classic AI plan-based

strategies

Systems Implemented

• GoDiS (Questions under Discussion,

Ginzburg ’96)

• PTT and EDIS (DRT)
• MIDAS (DRT)
• SRI Autoroute (Game Theory)