Transcript Konversationsanalys (CA) och kommunikationsreglering

Konversationsanalys (CA),
och kommunikationsreglering
Pragmatik VT04
Staffan Larsson
Conversation Analysis
• Etnologer: ”etnometdologi”
• Sacks, Schegloff, Jefferson
• Empiriska data
– audio (ofta telefonsamtal)
– video
– transkriptioner
• Empirisk metod
– Söker efter mönster i data och konstruerar regler för att förklara
dessa
• I motsats till traditionell lingvistik & pragmatik: intuitioner,
filosofisk spekulation, ”armchair linguistics”
• (Relativt) ickeformell metod
Typer av mönster funna inom CA
• makrostrukturer
– Närhetspar (Adjacency pairs)
– Preferensorganisation
– Presekvenser (Pre-sequences)
• ”local management systems”: lokal
reglering (subdialoger)
– Turtagning
– Reparationer
Närhetspar (adjacency pairs)
•
Sekvenser av 2 yttranden som är näraliggande och produceras av olika
talare
– Del 1 föregår del 2
– Dock ej nödvändigtvis direkt efter
•
Exempel
– fråga-svar
– hälsning-hälsning
– erbjudande-accepterande
•
Liknar dialogspel
– men annan metod
– ej uttryckt i grammatikform; ”lösare” struktur
•
Approximativ regel:
– Om A producerar den första delen i ett närhetspar, måste A sluta tala och B
måste producera parets andradel
•
Alternativ regel: konditionell relevans
– Om A producerar den första delen i ett närhetspar, så är dess andradel förväntad
och relevant
Preferensorganisation
• Problem med närhetspar:
– till varje förstadel svarar en mängd potentiella
andradelar
• T ex fråga ->
–
–
–
–
–
svar
protest
vidarebefodring (”Fråga Kalle”)
vägran att svara
ifrågasättande av ärlighet
• Lösning: preferensorganistation
– vissa andradelar är prefererade
• preferens är ej ett psykologiskt begrepp
– utan relaterat till ”markedness”
– prefererade andradelar är omärkta, ickeprefererade är märkta
• Vanliga kännetecken på ickeprefererad andradel:
–
–
–
–
föregås av försening, tvekljud etc
inledningsord som makerar ickepreferens (”Well...”, ”Tja...”)
åtföljs av förklaring till varför prefererad andradel ej gavs
innehåller avböjande komponent
• Exempel
– A: Kan du hjälpa mig?
– B1: visst (prefererat)
– B2: Äh njae jag har lite mycket att göra just nu
Pre-sekvenser
• ”förberedande frågor”
• Exempel 1
– T1
– T2a
– T3a
X: Är du upptagen ikväll?
Y: Nä, hurså?
X: Vill du följa med på bio?
• Exempel 2
– T1
– T2b
– T3b
X: Är du upptagen ikväll?
Y: Ja, jag ska tvätta håret. hurså?
X: Äh det var inget särskilt?
• T1 är en förberedande fråga som undersöker ett
förvillkor till den handling som T3 gäller
• T3 beror av T2, responsen på T1
Turtagning
• Observation: konversation karakteriseras
av turtagning (A och B: talare)
– A – B - A – B – A - ...
• Hur åstadkoms denna organisation?
– mindre än 5% överlapp
• Med hjälp av ett ”Local Management
System”!
– en uppsättning regler
– styr tillgång till ”the floor”, ung. rätten att tala
Turtagning: begprepp
• Tur (Turn Constructional Unit)
– en sekvens av syntaktiska enheter vars
gränser (främst) avgörs av syntaktiska (t ex
satsgränser) eller prosodiska faktorer
• TRP = Transition Relevance Place
– en punkt där turtagning kan ske
– TRP måste vara möjliga att förutse, för att
smidig turtagning ska vara möjlig
• Regel 1: Gäller initialt vid första TRP i varje tur
– (a) Om aktuell talare (A) väljer nästa talare (N) under
sin tur, måste A sluta och N börja tala vid första TRP
efter valet av N
– (b) Om A inte väljer N så kan vem som helst ta turen
vid nästa TRP (fri konkurrens)
– (c) Om A inte väljer N och ingen annan ”självväljer” så
kan A fortsätta
• Regel 2: Gäller vid efterföljande TRP i en tur
– När 1(c) har applicerats av A, så gäller 1(a)-(c) vid
nästa TRP, och rekursivt vid efterföljande TRP, tills
talarbyte inträffar
• Om någon bryter mot reglerna
– den som avbryter kan bli förmål för kritik (”Låt mig tala
till punkt!”)
– ”tävling”: ökande volym, lägre tempo, förlängda
vokaler, staccato etc. tills någon ger upp
• Kritik mot denna modell
–
–
–
–
Tar ej hänsyn till ickeverbala signaler
Vad är en TRP mer exakt?
Ej universell
Tar ej hänsyn till
• sociala roller & maktstrukturer
• institutionella turtagningssystem (t ex formella möten,
rättegång)
Turtagning i dialogsystem
• Strikt turtagning:
– Så länge systemet talar så kan användaren inte säga
något (systemet lyssnar inte)
– Så länge användaren (utan paus) talar gör systemet
inget; vid paus tar systemet över turn
• ”Barge-in”:
– Om användaren säger något då systemet talar så
slutar systemet tala
• Turtagning i dialog med flera deltagare, inklusive
dialogsystem (Fredik Kronlid)
Reparationer
•
Exempel
– A: Jag mötte Nils igår
– B: Vem sa du? [NTRI]
– A: Nils
•
TUR1
TUR2
TUR3
Next Turn Repair Initiator (NTRI)
– inbjuder till reparation av föregående tur
•
Typer av reparationer
– Självinitierad, utan NTRI
– Annan-initierad, med NTRI
•
Preferensordning
– Självinitierad i TUR1
• Jag mötte Nils äh Kalle igår
– Själviniterad efter TUR1 men före TUR2
• Jag mötte Nills igår. Äh Kalle mena ja
– Annaninitierad med NTRI i TUR2, självreparation i T3 (se överst)
– Annaniniterad annanreparation i T2
• A: Jag mötte Nils igår
• B: Du menar väl Kalle?
Grounding (Clark mfl)
• Not CA, but related area
• Common Ground (CG): shared knowledge about the
dialogue; utterances incrementally add to CG
• ”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
• Grounding is regulated by local communication
management systems (Allwood)
– ICM: grounding, sequencing, turntaking
– OCM: hesitations, self-corrections, ...
Clark’s grounding model
• Contribution types: Present, Accept
Accept
Present
S
1
• When does the presentation phase end?
– I: Move the boxcar to Corning
– I: and load it with oranges
– R: ok
F
Clark’s grounding model
• Contribution types: Present, Accept
Accept
Present
S
1
F
• When does the presentation phase end?
–
–
–
–
I: Move the boxcar to Corning
R: ok
I: and load it with oranges
R: ok
• Cannot be decided by just looking at the utterance; need
to look at next utterance
– not useful in realtime setting
Traum’s grounding model
• Discourse Units (DUs)
– unit of conversation at whicgh grounding takes place
– composed of individual utterance-level actions
(grounding-level acts, sub-DU acts)
• Some (sub-DU) acts
–
–
–
–
–
Initiate
Continue
Ack(nowledge)
Repair: correcting oneself or the other
Cancel: retraction, makes DU ungroundable (Ӏh
förresten det var inget”)
• act(I/R); I=initiator, R=responder
Continue(I)
Ack(R)
Initiate(I)
S
1
F
• This model is supplemented with an
information state update model
• adding self-repair and cancel
Continue(I), Repair(I)
Ack(R)
Initiate(I)
S
1
F
Cancel(I)
Cancel(I)
D
• adding self-repair and cancel
Continue(I), Repair(I)
Ack(R)
Initiate(I)
S
1
F
Cancel(I)
Cancel(I)
D
Feedback and grounding in
dialogue systems
ICM (Allwood)
• Interactive Communication Management
– As opposed to Own Communication Management (OCM): selfcorrections, 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.)
• Turntaking moves
ICM in current commercial
systems
• Usually, 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
• ”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
• We want to relate it to grounding in a system
Classifying feedback
•
•
•
•
•
Level of action
Polarity
Eliciting or non-eliciting
Form (syntactic realisation)
Content type (object- or metalevel)
Feedback levels
• 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
• Polarity (Allwood et.al. 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
Eliciting / nonelciting feedback
(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
• Rough correspondence / operationalisation
– Checking feedback is eliciting; explicitly raises grounding issue
– Positive feedback is noneliciting; may implicitly raise grounding
issue
• What about negative feedback?
– ”pardon?”,”huh?”: eliciting?
– ”I didn’t hear you”: noneliciting?
Object- or metalevel content
• 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
• 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.
Simplifying assumptions
regarding feedback
• We only represent action level and polarity
• Eliciting/noneliciting dimension implicit
– Negative feedback is eliciting in some sense; 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 in classification; decided by
generation module
• Metalevel / object level perhaps not so interesting unless
full compositional semantics are used
– ”Do you mean that you want to Paris?” vs. ”Do you want to go to
Paris?”
Formalising ICM dialogue moves
• Level
–
–
–
–
–
con: contact
per: perception
sem: semantic understanding (no context)
und: pragmatic understanding (relevance in context)
acc: acceptance
• Polarity
– pos: positive
– neg: negative
– chk: checking
Feedback move notation
• icm:Level*Polarity{:Args}
• Examples
–
–
–
–
–
–
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”
GoDiS: an issue-based
dialogue 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
ICM: feedback and grounding, sequencing
Question accommodation, re-raising, clarification
Inquiry-oriented, action-oriented, negotiative dialogue
System feedback for user
utterances in GoDIS
• 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]
System feedback, cont’d
• 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]
User feedback for system
utterances in GoDiS
• contact: • perception
– negative: fb-phrase (”Pardon?”, ”I didn’t hear what you said”)
[icm:per*neg]
• understanding: • acceptance/integration
– negative: fb-phrase (”I don’t know”, ”Never mind”) [icm:acc*neg]
– positive: fb-word (”okay.”) [icm:acc*pos]
Feedback selection
•
Feedback polarity selected depending on:
1.
2.
3.
4.
Contact: Whether any speech is observed
Perception: Speech recognition score > threshold
Semantics: Whether system can find a non-contextual
interpretation
Pragmatic understanding: Whether system can find a relevant
contextual interpretation
–
–
–
–
5.
•
none: extremely high score (certain of interpretation)
Positive: high score (pretty sure of interpretation)
Checking: medium score (not so sure)
Negative: low score (very unsure)
Acceptance: Whether system can accept what has been said
General principles
–
–
Produce positive feedback only on highest possible level
When producing negative feedback on level N, produce positive
feedback on level N-1
Feedback on multiple levels
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?
Positive
perception
Negative
perception
feeback
Negative
understanding
U> siridus
S> I heard you say siridus . Sorry, I dont understand. What can I
do for you?
Positive
understanding
(word meaning)
Negative
understanding
(relevance)
U> channel one
S> channel one. I dont quite understand. Do you want to add a
program or change channel?
(Task
clarification)
Positive
understanding
Rejection
(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?”
User negative
perception
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.
System
repetition
Positive
acceptance
Reactions to positive and
checking feedback
• After check feedback,
– (e.g., ”channel one, is that correct?”)
– positive response is needed, or system will assume it
was wrong
• After positive feedback,
– (e.g., ”channel one.”)
– if user gives no response or positive response,
system continues to assume it was right;
– If user gives negative response, system assumes it
was wrong
• correcting the system
Correcting the 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.
Positive
feedback
U> no
S> not channel five. So, WhatNegative
channel do you want?
answer to fb.
U> channel six
S> Okay. channel six.”
Issue-based grounding
• Checking feedback on und-level explicitly raises understandingissue
– icm:und*chk:C raises ?und(C)
• ”Is C the meaning of the previous utterance?”
– Positive response leads to adding C to shared commitments
– Negative or no response leads to no action
• Positive understanding feedback does not raise the understandingissue explicitly
– In fact, tentatively assumes it has been positively resolved
– but makes it available for interpretation of short answers
• in this case, ”yes” or ”no”
– Negative reponse leads to retracting C
– Positive or no response leads to no action
• So far, only implemented for understanding level
ISSUES, QUD and accommdation
• We distinguish QUD and ISSUES:
– QUD (local): Questions available for resolution of short
answers
– ISSUES (global): Issues/questions that have been raised but
not yet resolved
• QUD-to-ISSUES accommodation
– If an answer is given which does not address any question
on ISSUES,
– But does address a question Q on QUD
– Then, accommodate Q to ISSUES (this amounts to raising
Q)
Feedback, ISSUES and QUD
• Assume previous move had content C
• Checking feedback
– Push ?und(C) on ISSUES and QUD
• Positive feedback
– Add C to shared commitments
– Push ?und(C) on QUD (but not on ISSUES)
– ”yes” or ”no”  do QUD-to-ISSUES accommodation
• Integrating responses to understanding-issues
– Done by a single rule, regardless of how the understanding-issue was
raised
– Given that ?und(C) is on ISSUES,
– ”yes”  add C to shared commitments if not already there
– ”no”  retract C from shared commitments if it’s there (actually,
backtrack to saved previous shared commitments)
Negative response to positive
feedback
S> Lets see. What channel do you want?
U> channel six
S> OK,
channel five.
channel (5) added to shared commitments;
?und(channel (5)) on QUD
U> no
QUD-to-ISSUES accommodation
 ?und(channel (5)) on ISSUES
integrate ”no”
 retract channel(5)
S> not channel five. So, What channel do you want?
Negative response to cheking
feedback
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> channel
five?
?und(channel (5)) on ISSUES and QUD
U> no
integrate ”no” ( do nothing)
S> So, What channel do you want?
U> channel six
S> Okay. channel six.”
Sequencing ICM
• 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 correlate them with updates to the common
ground
Sequencing moves generated
by GoDiS
• Formal notation schema:
– icm:Type{:Content}
• Loading a dialogue 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
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 ?
Reraising an issue
S> (…) Lets see. What country are you from?
explicitly
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?
Sequencing ICM:
Accommodation
S> Lets see. What can I do for you?
U> channel five today
Signals accommodation
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. ”
Future work
• 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
• Extend issue-based grounding to all levels
Summary of ICM and grounding in
GoDiS
• 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
• Issue-based grounding provides mechanisms
allowing the user to react to system feedback
• Sequencing moves can be correlated with updates to
common ground, and used to signal these updates to
the user
Relation to Traum’s computational
theory of grounding
• Traum puts focus on positive feedback and
corrections (self and other)
– Deals with the question, when does a contribution end?
Related to turntaking.
– Focus on self- and other-corrections (not included here);
involves turntaking and OCM, but also feedback
– Does not include sequencing ICM
– Based on the TRAINS corpus of H-H dialogue -> (arguably)
focus on positive feedback
• Focus on understanding-level
– ”grounding” here refers only to the understanding level
– Acceptance and rejection seen as ”core speech acts”
Implicit feedback?
• Clark: ”relevant followup” to U counts as positive
feedback
– 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 (a
cautious assumption)
• 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?
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!”
OCM: Own Communication
Management
• Egenkommunikationsreglering
• Till nästa gång
Uppgifter
• 1. Hur fungerar turtagning enligt CA-analysen? Hitta på
några dialoger som exemplifierar olika
turtagningssituationer och förklara dessa utifrån CAreglerna för turtagning.
• 2. Titta i TV-tablån och bestäm dig för ett TV-program
som du vill spela in. Ha penna och papper (eller dator)
redo. Ring upp Videoapplikationen i GoDiS på 7731978
och försök programmera videon att spela in ditt program.
Anteckna allt som sägs i dialogen (det går rätt långsamt,
så man hinner med). Vilka typer av ICM (grounding och
sequencing) förekommer i dialogen?
– Observera att systemet funkar rätt dåligt just nu, p g a diverse
tekniska problem. GoDiS är egentligen mycket bättre än såhär!
I dialog med en miniräknare
•
Uppgift: Fundera över följande:
– Hur skulle talad interaktion med en
vanlig enkel miniräknare kunna se
ut?
– Aspekter att fundera över:
Talsyntes
Taligenkänning
•
•
•
•
Turtagning
Tvekljud
Självreparation
Återkoppling
– Innan torsdagens föreläsning:
Försök att designa ett ‘dialogspel’
som inbegriper dessa fenomen!
– Ge konkreta exempel i form av små
transkriptioner, t.ex.:
U: 2+2
+1
S:
4
5
va?
5
– Skriv en sida om din design. De som
gör detta tillräckligt bra slipper fler
uppgifter i samband med min
föreläsning.