Dialog Models

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Dialog Models

• 11-716 September 18, 2003
• Thomas Harris

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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.

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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.

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Attentions, Intentions, and the Structure of
Discourse Barbara J. Grosz and Candance L.
SidnerComputational Linguistics, vol. 12, num
3, July-September 1986

• 11-716
• Ariadna Font Llitjos
• September 25, 2001

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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

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• This distinction simplifies both the explanations
  given computation mechanism used
• Speaker/hearer ICP/OCP

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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

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Intentional Structure

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

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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 on DSPs, i.e. a dominance hierarchy
• Determinations (complete specification of what is
  intended by whom) vs. recognition

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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

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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 of entities in each space during the
  corresponding segments of the discourse

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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

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Discourse examples

• Essay (p. 183)
• Task-oriented dialog (p. 186)
• Intentional structure is neither identical nor
  isomorphic to the general plan

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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
  operate 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

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• Info constraining DSP
• Specific linguistic markers
• Utterance-level intentions (Grices 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)

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Properties and problems of discourse-level
intentions

• DP/DSP are natural extensions of Grices
  utterance-level meanings but GS dont address
  meaning
• Remains to be seen whether x and f are equivalent
  to DS and their features (p. 199)
• GS state that the modes of correlation that
  operate at the utterance-level (c) also function
  at the discourse level

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Basic Generalization

• Discourse sufficiency the intentional structure
  need not be complete
• Belief case
• Action case

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Conclusions

• Theory presented by GS is a generalization of
  theories of task-oriented dialogs, but its
  domain independent
• Interesting and thorough but infeasible

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More conclusions

• Asks more questions than it answers.
• How do we implement these aspects of dialog?
• Basically correct.

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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

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Basic Toolkit Architecture

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

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Informational Components

• Data
• Participants
• Beliefs
• Common ground
• Intentions

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Formal Representations

• Formal representation of informational components
• Typed feature structures
• Lists
• Sets
• Propositions
• First order logic

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Dialog Moves

• Trigger the update of the information state
• Grammatical triggers
• External events

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Update Rules

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

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Control Strategy

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

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Dialog Theories

• Finite State Dialog Models
• Plan-based Models

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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

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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

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Systems Implemented

• GoDiS (Questions under Discussion, Ginzburg 96)
• PTT and EDIS (DRT)
• MIDAS (DRT)
• SRI Autoroute (Game Theory)