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Generating Feedback and Sequencing Moves in a Dialogue System. AAAI Spring Symposium 2003 Staffan Larsson Göteborg University, Sweden. Overview. Interactive Communication Management (ICM) ”Verification” in dialogue systems Classifying and formalising ICM ICM for a dialogue system Examples

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Generating feedback and sequencing moves in a dialogue system

Generating Feedback and Sequencing Moves in a Dialogue System

AAAI Spring Symposium 2003

Staffan Larsson

Göteborg University, Sweden

Overview System

  • Interactive Communication Management (ICM)

  • ”Verification” in dialogue systems

  • Classifying and formalising ICM

  • ICM for a dialogue system

  • Examples

  • Conclusions & Future work

Icm allwood
ICM (Allwood) System

  • Interactive Communication Management

    • As opposed to Own Communication Management (OCM): self-corrections, hesitations, etc.

  • Feedback moves

    • (short) utterances which signal grounding status of previous utterance (”mm”, ”right”, ”ok”, ”pardon?”, ”huh?” etc.)

  • Sequencing moves

    • utterances which signal dialogue structure (”so”, ”now”, ”right”, ”anyway” etc.)

    • Dialogue structure part of / modeled by common ground

  • Turntaking moves

Grounding and icm in current commercial systems
Grounding and ICM in current commercial systems System

  • Limited to ”verification”

  • Examples (San Segundo et. al. 2001)

    • I understood you want to depart from Madrid. Is that correct? [”explicit v.”]

    • You leave from Madrid. Where are you arriving at? [”implicit v.”]

  • Involves repetition or reformulation

  • Appears in H-H dialogue, but not very common

From verification to icm in dialogue systems
From verification to ICM in dialogue systems System

  • ”Verification” is just one type of ICM behaviour

    • Perhaps the one most cruicial in dialogue systems given poor speech recognition

  • Could a wider range of the ICM behaviour occurring in H-H dialogue be useful in dialogue systems?

  • We want a typology of ICM moves for H-H dialogue

    • Feedback and sequencing moves

  • We want to formalise it and use it in a system

    • Still we will implement only a subset, but more than verification

Classifying feedback
Classifying feedback System

  • Level of action

  • Polarity

  • Eliciting / noneliciting

  • Form (syntactic realisation)

  • Content type: object- or metalevel

Feedback levels
Feedback levels System

  • Action levels in dialogue (Allwood, Clark, Ginzburg)

    • Contact: whether a channel of communication is established

    • Perception: whether DPs are perciveving each other’s utterances

    • Understanding: Whether DPs are understanding each other’s utterances

      • Non-contextual (”semantic”) meaning

      • Contextual (”pragmatic”) meaning

    • Acceptance: Whether DPs are accepting each other’s utterances

  • The function of feedback is to signal the status of utterance processing on all levels

Feedback polarity
Feedback polarity System

  • Polarity (Allwood 1992)

    • Positive: indicates contact, perception, understanding, acceptance

    • Negative: indicates lack of contact, perception, understanding, acceptance

    • We add a ”neutral” or ”checking” polarity – there is one or more hypotheses, but the DP lacks confidence in them

  • Examples

    • ”I don’t understand”: negative

    • ”Do you mean that the destination is Paris?”: checking

    • ”To Paris.”: positive

    • ”Pardon”: negative

Formalising icm dialogue moves
Formalising ICM dialogue moves System

  • Action levels

    • con: contact

    • per: perception

    • sem: semantic understanding (no context)

    • und: pragmatic understanding (relevance in context)

    • acc: acceptance

  • Polarity

    • pos

    • neg

    • chk (”int” in paper)

Feedback move notation
Feedback move notation System

  • icm:Level*Polarity{:Args}

    • icm:per*pos:String – ”I heard you say ’londres’”

    • icm:und*neg – ”Sorry, I don’t understand”

    • icm:und*chk:AltQ – ”Do you mean x or y?”

    • icm:und*pos:P – ”To Paris.”

    • icm:acc*neg:Q – ”Sorry, I can’t answer Q”

    • icm:acc*pos – ”Okay”

System feedback for user utterances in godis
System feedback for user utterances in GoDIS System

  • contact

    • negative (”I didn’t hear anything from you.”, ”Hello?”) [icm:con*neg]

  • perception

    • negative: fb-phrase (”Pardon?”, ”I didn’t hear what you said”) [icm:per*neg]

    • positive: repetition (”I heard ’to paris’”) [icm:per*pos:String]

  • semantic understanding:

    • negative: fb-phrase (”I don’t understand”) [icm:sem*neg]

    • positive: reformulation (”Paris.”) [icm:sem*pos:Content]

    • checking: reformulation (”Paris, is that correct?”, ”Paris?”) [icm:sem*chk:Content]

System feedback cont d
System feedback, cont’d System

  • pragmatic understanding

    • negative: fb-phrase (”I don’t quite understand”) [icm:und*neg]

    • positive: reformulation (”To Paris.”) [icm:und*pos:Content]

    • checking: reformulation (”To Paris, is that correct?”, ”To Paris?”) [icm:und*chk:Content]

  • acceptance/integration

    • negative:fb-phrase with reformulation (”Sorry, I cannot answer Q”, ”Sorry, Paris is not a valid destination city.”) [icm:acc*neg:Content]

    • positive: fb-word (”okay.”) [icm:acc*pos]

Feedback selection
Feedback selection System

  • Feedback polarity selected depending on (for each level respectively):

    • Contact: Whether any speech is observed

    • Perception: Speech recognition score

    • Semantics: Whether system can find a non-contextual interpretation

    • Pragmatic understanding: Whether system can find a relevant contextual interpretation

    • Acceptance: Whether system can accept what’s been said

Feedback on multiple levels
Feedback on multiple levels System

Negative perception feeback

S> Lets see. What can I do for you?

U> (mumble mumble)

S> Sorry, I didnt hear what you said. What can I do for you?

U> siridus

S> I heard you say siridus . Sorry, I dont understand. What can I

do for you?

U> channel one

S> channel one. I dont quite understand. Do you want to add a

program or change channel?

Positive perception

Negative understanding

Positive understanding (word meaning)

Negative understanding (relevance)

(Task clarification)

Generating feedback and sequencing moves in a dialogue system

Positive System



(negative acceptance feedback)

U> turn on the t v

S> turn on the TV… Sorry, I cannot control the TV set. Do you want to add a program or change channel?”

U> pardon

S> Sorry, I cannot control the TV set. Do you want to add a program or change channel?

U> change channel

S> Okay.

User negative perception

System repetition



Sequencing icm
Sequencing ICM System

  • Discourse particles

    • ”so” may be used to reraise a previously discussed question

    • ”right”, ”anyway”, ”let’s see…”

  • Verbose sequencing

    • ”Let’s talk about …”, ”Let’s return to the issue of …”

  • How do we classify these?

    • We will correlate them with updates to the common ground

Sequencing moves generated by godis
Sequencing moves generated by GoDiS System

  • Formal notation schema:

    • icm:Type{:Content}

  • Loading a plan

    • icm:loadplan – ”let’s see.”

  • Question accommodation

    • icm:accommodate – ”alright.”

  • Reraising an issue

    • icm:reraise – ”so, ”

    • icm:reraise:Q – ”returning to the issue of …”

Sequencing icm reraising issue loading a plan
Sequencing ICM: reraising issue, loading a plan System

Signals loading a plan

S> Welcome to the travel agency!

U> price information

S> (…) Lets see. How do you want to travel?

U> by flight

S> (…) What city do you want to go to?

U> paris

S> (…) What city do you want to go from?

U> do I need a visa ?

S> (…) Lets see. What country are you from?

U> sweden

S> Okay. Yes, you need a Visa.

S> Returning to the issue of price. Lets see. What city do you want to go from?

Reraising an issue explicitly

Sequencing icm accommodation
Sequencing ICM: Accommodation System

S> Lets see. What can I do for you?

U> channel five today

S> Alright. add a program… Lets see. Okay. channel five… today… What time do you want to start recording?

U> from six thirty to seven thirty

S> Okay. from six thirty… to seven thirty… The program has been added. ”

Signals accommodation

Conclusions System

  • Current dialogue systems use only a fraction of the range of ICM used by humans

  • By extending the range of ICM used by systems, their communication becomes more natural and comprehensive

  • We have provided an initial classification of feedback and sequencing ICM useful in a dialogue system, and implemented it

  • (ICM can be correlated with updates to common ground, and used to signal these updates to the user)

Future work
Future work System

  • Replace current ad-hoc forms based on corpus studies and existing work

    • ”discourse markers” (Schiffrin)

    • ”cue phrases” (Grosz & Sidner and others)

  • ”Real” generation rather than templates

    • Integrate ICM with other utterances, rather than just appending them

  • Explore other ways of generating ICM

    • Intonation, facial expression, etc.

  • Extend the range of ICM generated (and interpreted) by the system

Questions? System

Object or metalevel content
Object- or metalevel content System

  • Utterances with metalevel content explicitly refer to contact, perception, understanding or acceptance

  • Object-level utterances instead refer to the task at hand

  • Example

    • S: What city are you going to?

    • U: Paris

    • S(1a): Did you say you’re going to Paris? [meta]

    • S(1b): Are you going to Paris? [object]

    • S(2a): Do you mean Paris, France or Paris, Texas?

    • S(2b): Do you want to go to Paris, France or Paris, Texas?

  • This dimension does not apply to all feedback, e.g. ”Paris.”, ”Pardon?”

  • (Is 2b feedback or simply an alternative question?)

Realisation of feedback moves
Realisation of feedback moves System

  • Syntactic form:

    • declarative: ”I didn’t hear what you said.”; ”The destination city is Paris.”

    • interrogative: ”What did you say?”; ”Do you want to go to Paris?”

    • imperative: ”Please repeat your latest utterance!”

    • elliptical

      • interrogative: ”Paris?”, ”To Paris or from Paris?”

      • declarative: ”To Paris.”

  • In general, the exact formulation of ICM phrases may depend on various contextual factors

    • including activity, noise level, time constraints etc.

Correcting the system
Correcting the system System

S> Lets see. What can I do for you?

U> add program

S> Okay. Add a program…

S> Lets see. What channel do you want?

U> channel six

S> OK, channel five.

U> no

S> not channel five. So, What channel do you want?

U> channel six

S> Okay. channel six.”


Interrogative feedback

Negative answer to fb.

Signals reraising an issue (Sequencing ICM)

Reactions to positive and checking feedback
Reactions to positive and checking feedback System

  • After positive feedback, system leaves a pause for the user to agree or disagree

    • if user gives no response, system assumes it was right

  • After check feedback, positive response is needed

    • or system will assume it was wrong

Implicit feedback
Implicit feedback? System

  • Clark: ”relevant followup” to U

    • What is relevant?

      • simple cases for followups to questions:

        • answer to question

        • ”subquestion”

        • feedback concering question

      • Complex cases: all other utterances

    • In general, complex inference and knowledge may be needed (implicatures)

    • Currently, irrelevant followup counts as negative feedback

  • What about no followup at all?

    • in reaction to ask-move or interrogative feedback, counts as negative

    • in reaction to answer or positive feedback, counts as positive

Rejection? System

S: ”Where do you want to go?”

U1: ”Nowhere”

U2: ”I don’t know”

  • Should these count as rejections?

    • U1: negative answer? presupposition failiure? rejection?

    • U2: rejection?

      • but not as definite as ”No comment!”

Relation to traum s computational theory of grounding
Relation to Traum’s computational theory of grounding System

  • Focus on understanding-level

    • ”grounding” here refers only to the understanding level

    • Acceptance and rejection seen as ”core speech acts”

  • Focus on positive feedback and corrections (self and other)

    • Based on the TRAINS corpus of H-H dialogue

    • Deals with the question, when does a contribution end?

    • Corrections not included here; involves turntaking and OCM

  • Does not include sequencing ICM

Godis an issue based dialogue system
GoDiS: an issue-based dialogue system System

  • Explores and implements Issue-based dialogue management (Larsson 2002)

    • Based on Ginzburg’s notion of a dialogue gameboard involving Questions Under Discussion (QUD)

    • Uses (mostly pre-scripted) dialogue plans

  • Extends theory to more flexible dialogue

    • Multiple tasks, information sharing between tasks

    • Feedback and grounding

    • Question accommodation, re-raising, clarification

Eliciting nonelciting feedback
Eliciting / nonelciting feedback System

  • (Allwood et. al. 1992)

  • Eliciting feedback is intended to evoke a response from the user

  • Noneliciting feedback is not so intended

    • But may nevertheless recieve a response

Simplifying assumptions regarding feedback
Simplifying assumptions regarding feedback System

  • We only represent action level and polarity

  • In polarity, we replace ”neutral” by ”checking”

    • We exclude feedback which is neutral but not check-questions

  • Eliciting/noneliciting dimension implicit

    • Negative feedback is eliciting; since something went wrong, it must be fixed

    • Checking feedback is also eliciting, since it poses a question that must be adressed

    • Positive feedback is not eliciting (we assume)

  • Syntactic form not included

Grounding System

  • ”To ground a thing … is to establish it as part of common ground well enough for current purposes.” (Clark)

  • making sure that the participants are percieving, understanding, and accepting each other’s utterances