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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

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Konversationsanalys (CA), och kommunikationsreglering

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  1. Konversationsanalys (CA), och kommunikationsreglering Pragmatik VT04 Staffan Larsson

  2. 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

  3. Typer av mönster funna inom CA • makrostrukturer • Närhetspar (Adjacency pairs) • Preferensorganisation • Presekvenser (Pre-sequences) • ”local management systems”: lokal reglering (subdialoger) • Turtagning • Reparationer

  4. 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

  5. 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

  6. 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

  7. Pre-sekvenser • ”förberedande frågor” • Exempel 1 • T1 X: Är du upptagen ikväll? • T2a Y: Nä, hurså? • T3a X: Vill du följa med på bio? • Exempel 2 • T1 X: Är du upptagen ikväll? • T2b Y: Ja, jag ska tvätta håret. hurså? • T3b 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

  8. 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

  9. 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

  10. 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

  11. 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)

  12. 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)

  13. Reparationer • Exempel • A: Jag mötte Nils igår TUR1 • B: Vem sa du? [NTRI] TUR2 • A: Nils 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?

  14. 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, ...

  15. Clark’s grounding model • Contribution types: Present, Accept • When does the presentation phase end? • I: Move the boxcar to Corning • I: and load it with oranges • R: ok S 1 Accept F Present

  16. Clark’s grounding model • Contribution types: Present, Accept • 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 S 1 Accept F Present

  17. 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 (”Äh förresten det var inget”)

  18. act(I/R); I=initiator, R=responder • This model is supplemented with an information state update model Continue(I) S 1 Ack(R) F Initiate(I)

  19. adding self-repair and cancel Continue(I), Repair(I) S 1 Ack(R) F Initiate(I) Cancel(I) Cancel(I) D

  20. adding self-repair and cancel Continue(I), Repair(I) S 1 Ack(R) F Initiate(I) Cancel(I) Cancel(I) D

  21. Feedback and grounding in dialogue systems

  22. ICM (Allwood) • 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.) • Turntaking moves

  23. 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

  24. 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

  25. Classifying feedback • Level of action • Polarity • Eliciting or non-eliciting • Form (syntactic realisation) • Content type (object- or metalevel)

  26. 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

  27. 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

  28. 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?

  29. 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?)

  30. 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.

  31. 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?”

  32. 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

  33. 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”

  34. 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

  35. 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]

  36. 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]

  37. 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]

  38. Feedback selection • Feedback polarity selected depending on: • 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 • 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

  39. 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? 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? Negative perception feeback Positive perception Negative understanding Positive understanding (word meaning) Negative understanding (relevance) (Task clarification)

  40. 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?” 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 Positive acceptance

  41. 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

  42. 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. U> no S> not channel five. So, What channel do you want? U> channel six S> Okay. channel six.” Positive feedback Negative answer to fb.

  43. Issue-based grounding • Checking feedback on und-level explicitly raises understanding-issue • icm:und*chk:Craises ?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 understanding-issue 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

  44. 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)

  45. 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)

  46. 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?

  47. 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.”

  48. 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

  49. 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 …”

  50. 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 ? 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

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