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Dialogue act theory
Volha PetukhovaSaarland University
Einführung in Diskurs and Pragmatik, Sommersemester 2015
Einführung in Diskurs and Pragmatik, Sommersemester 2015
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Outline
• Introduction: Austin and Searle• Dialogue act concepts• Dialogue act taxonomies• Dialogue act annotation• Dialogue act recognition
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Introduction• Logical Positivism (1930s): A sentence is only meaningful if it can
be verified (i.e. tested for truth and falsity)
• Wittgenstein 1958: “Meaning is use": Utterances are only explicable in relation to the activities, or language-games, where they participate.
• Austin 1962: How to do things with words: “The total speech act in the total speech situation is the only actual
phenomenon which we are engaged in elucidating” Sets out to demolish the view of language that makes truth-conditions central to language understanding. Rather, see what acts are performed by utterances.
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Austin’s argumentationArgues that truth-conditions are NOT central to language understanding. Rather
language use is. Utterances not only say things, they do things.• Austin's Argumentation:1. Distinction between constatives (Konstativen) (sentences used to make true/false
statements) and performatives (Performativen) sentences that change the state of the world) on the basis of linguistic form.
2. Performatives cannot be false, but they can fail to do things when their felicity conditions (Gelingensbedingungen) are not fullfilled. Note: constatives also have felicity conditions!
3. Performatives are not a special class of sentences. Some sentences explicitly performative, others can be implicitly so.
4. The dichotomy between constatives and performatives does not really exist. Rather, they are each a special case of a set of illocutionary acts (illokutionäre Akte).
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Constative vs. Performative Sentences• Constatives: used to make true/false statements or assertions
(1) Schnee ist grün. Snow is green.
• Performatives: used to change the world. Performatives are ordinary declarative sentences which are not used with any intention of making true or false statements. (They are not true/false.)
(2) Ich wette mit dir, da es morgen regnet. I bet you 50 pence it will rain tomorrow.
(3) Ich entschuldige mich. I apologize.
(4) Ich erhebe Einspruch. I object.
(5) Ich vermache dir meinen Rembrandt. I bequeath to you my Rembrandt.
(6) Ich warne dich! I warn you.
(7) Ich taufe dieses Schiff auf den Namen “Anna”. I christen this ship the Anna.
(8) Hiermit erkäre ich Sansibar den Krieg. I hereby declare war on Zanzibar.
(9) Ich erkläre Sie hiermit zu Mann und Frau. I hereby declare you man and wife.
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Explicit vs. Implicit Performatives• Explicit Performatives have a specific linguistic structure, i.e. The
Performative Normal Form (PNF): 1st person singular, present tense, allows “hereby", “performative" main verb, etc.(11) Ich warne Sie (hiermit). I (hereby) warn you.
(12) ??Ich schlage jetzt hiermit die Eier schaumig. (no performative verb)
• Implicit Performatives: However, a sentence that does not have all (or any) features of PNF can nevertheless function as a performative. Examples:
(13) Sie sind hiermit gewarnt! (not 1. Person Sg.)(14) Achtung! (no PNF features)(15) Du wirst dir noch die Finger verbrennen! (no PNF features)
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Theory of Speech Acts (Sprechakttheorie)
• All utterances have both a (propositional) meaning (they say things) and a force (they do things). A theory should clarify in what ways, by uttering sentences, one might be said to be performing actions.
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Speech Act TypesAustin distinguishes three kinds of acts an utterance simultaneously
performs:– Locutionary Act/ Lokutionärer Akt: The utterance of a sentence with a
particular sense and reference. (e.g., I will come back.)
– Illocutionary Act/ Illokutionärer Akt: the making of a statement, offer, promise etc. in uttering a sentence, by virtue of the conventional force associated with it. (e.g., a promise, or a threat etc.)
– Perlocutionary Act/ Perlokutionärer Akt: bringing about effects on the audience by means of uttering the sentence, such effects being special to the circumstances of utterances. (e.g., making hearer happy, angry, or scared etc.)
In practice, the term speech act has come to refer exclusively to the illocutionary act.
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Searle
Searle’s further development of Speech Act Theory:
• relates illocutionary force to Grice's communicative intention (Bedeutung-nn)
• felicity conditions are not only dimensions along which an expression can go wrong, but also serve to distinguish different kinds of illocutionary forces
• classification of speech acts
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Felicity conditions (according to Searle)
propositional content, preparatory preconditions, sincerity conditions, essential condition
– Ich verspreche, dass ich morgen vorbeikomme/I promise I will come tomorrow
1. The speaker said (prop. content) he would perform a future action.
2. S intends to come (sincerity)
3. S believes he can do it (preparatory)
4. S thinks he wouldn't do it anyway, under normal conditions (preparatory)
5. S thinks that H wants him to come (preparatory)
6. S intends to obligate himself to come by uttering U (essential)
7. Both S and H understand U
8. They are both conscious, normal human beings
9. They find themselves in a normal situation (e.g. not acting in a play)
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Searle's Classication of Speech Acts
Searle groups illocutionary acts into ve basic kinds:• Representatives: commit the speaker to the truth of the
expressed propositions (e.g. asserting, concluding)• Directives: attempt by the speaker to get the hearer to do
something (e.g. request, question)• Commissives: commit the speaker to some future course of
action (e.g. promise, offer, threat)• Expressives: express a psychological state (e.g. Thanks,
apologies, welcome, congratulation)• Declarations: effect changes in the institutional state of
affairs (e.g., declaring war, christening)
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Direct and Indirect Speech acts• Examples
(16) Mach bitte die Tür zu! (Imp)Direct speech act: Request to shut the door.
There are many other possible forms which have various direct speech acts, but all have the request to shut the door as an indirect speech act:
(17) Ich möchte, dass du die Tür schliet. (Decl)(18) Ich wäre dir sehr dankbar, wenn du die Tür schlieen würdest. (Decl)(19) Are you able by any chance to close the door? (Int)(20) Would you close the door? (Int)(21) Won't you close the door? (Int)(22) Hast du die Tür vergessen? (Int)(23) Wie wäre es mit etwas weniger Durchzug? (Int)(24) Nun, Julia, was tun grosse Leute, wenn sie hereinkommen? (Int)
In day-to-day speech, most usages are indirect.
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Complications?
But:A1: Well we can chat away for ... um... for five
minutes orso I think at... B: Mm-hmm A1: ... at most
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Complications? (cont.)
Or
A1: Like you said time to market was a problem and how many components are physically in there in cost
A2: um (0.4)A3: 0.28 and (0.12) the power is basically a factor of thatA4: 0.55 um (0.47)A5: and (0.32) the lower components: the power, the logic, the
transmitter and the infrared, they affect you in terms of the size of your device
A6: 0.59 um (0.26)A7: and (0.16) that would have some impact on how y i think
more hold rather than the actual use the remote control
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Complications? (cont.)
About half ... about a quar- ... th- ...third of the way down I have some hills
Because twenty five Euros for a remote... how much is that locally in pounds? is too much money to buy an extra remote or a replacement remote
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Complications? (cont.)
Spontaneous speech is ungrammatical and not fluent:– Not complete sentences– filled/unfilled pauses, stalling– restarts, self-corrections– phrasal interjections– interruption & continuation
As a consequence, a (meaningful) unit can be:
• discontinuous• spread over multiple turns
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Modern account
Dialogue behaviour is governed by three fundamental principles:
• Rationality• Cooperativity • Sociality
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Modern account
• Rationality: dialogue participants act rationally in trying to achieve their goals, using their communicative resources effectively and efficiently
• Cooperativity: dialogue participants act not only in the interest of their own goals, but also in the interest of those of their dialogue partners
• Sociality: communication is a form of social behaviour, subject to norms and conventions of social interaction
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Modern account
A dialogue can be viewed as a sequence of sets of actions (‘dialogue acts’) which are intended to change the information state of the addressee.
A dialogue act captures the speaker’s intention and the associated beliefs of the speaker about the addressee and about the world.
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Basic concepts
• Modelling dialogue interaction
Communication is a complex activity
• Theory of meaning and a theory of dialogue
Meaning is a dynamic notion, defined by the use of language in communication
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What’s a Dialogue ActDefinition: (not just a speech act, used in dialogue)A dialogue act is a unit in the semantic description
of communicative behaviour in dialogue, specifying how the behaviour is intended to change the information state of the addressee through his interpretation of the behaviour.
Aspects of a dialogue act: - communicative function - semantic content
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Types of dialogue acts
- “What did you say?” type of dialogue act? - feedback act - question
- “I didn’t hear what you said” type of dialogue act? - feedback act - inform
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Multifunctionality
1. U: Can you tell me what time is the first train to the airport on Sunday?
2. S: On Sunday morning the first train to the airport is at 5.32
3. U: Thank you.
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Multifunctionality
1. U: Can you tell me what time is the first train to the airport on Sunday?
2. S: On Sunday morning the first train to the airport is at 5.32
3. U: Thank you. - expression of thanks
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Multifunctionality
1. U: Can you tell me what time is the first train to the airport on Sunday?
2. S: On Sunday morning the first train to the airport is at 5.323. U: Thank you.
- expression of thanks - positive feedback (about understanding and
acceptance)
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Multifunctionality
1. U: Can you tell me what time is the first train
to the airport on Sunday?2. S: On Sunday morning the first train to
the airport is at 5.323. U: Thank you.
- expression of thanks - positive feedback (about understanding and
acceptance) - indication of dialogue closure
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General-purpose functions
Example: Informs in various dimensions:
• The KL204 leaves at 12.30. Task/domain• I see what you mean. Auto-feedback• You misunderstood me. Allo-feedback• I would like to hear Peter’s opinion. Turn management• I’m listening. Contact management• ... I mean Toronto. Own communication management• I would like to ask you something. Discourse structuring• I’m very grateful for you help. Social obligation
management
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Dimensions
Examples:
1. Auto-feedback OverallPositive Okay.2. Allo-feedback EvaluationElicitation Okay?3. Turn management TurnGiving Yes4. Time management Stalling Well, you know,..5. Contact man’t (optional) ContactChecking Hello? 6. Own comm. man’t Self-correction I mean...7. Partner comm.man. Completion ... completion8. Dialogue structuring DA-announcement Question: 9. Social oblig. man’t Valediction Bye10. Task/domain OpenMeeting I open this meeting
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Segmentation
Set QuestionU : what time is the first train to the
airport on Sunday? Set AnswerS : at ...ehm... 6.17 S : at ...ehm... 6.17
SetAnswer STALLINGSetAnswer
STALLING
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Segmentation
U : what time is the first train to the airport on Sunday?
S : the first train to the airport on Sunday is at 6.17 SetAnswer
FEEDBACK
no single segmentation exists that indicates the relevant functional segments
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Segmentation
About half ... about a quar- ... th- ...third of the way down
Because twenty five Euros for a remote... how much is that locally in pounds? is too much money to buy an extra remote or a replacement remote
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Segmentation: what is the smallest meaningful dialogue unit?
• Segmentation of spoken dialogue is nontrivial due to phenomena such as:
• filled/unfilled pauses, stalling• restarts, self-corrections• phrasal interjections• interruption & continuation
As a consequence, a meaningful unit can be:
• discontinuous• spread over multiple turns
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Multiple segmentations
• Solution: use multiple segmentations instead of a single one
• Allows indication of multiple functional segments in an
utterance to be identified more accurately
• Compatible with DA taxonomies that address several aspects (‘dimensions’) of dialogue simultaneously
(e.g. DAMSL, DIT and ISO 24617-2)
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Method: segmentation
INFORM
Propositional Question
Pos. to A1
Assign to A
Set Question
Assign Assign to C
Pos. exe B2Neg. exe A1
Propositional Question to A1
Accept Assign A
A1: We’re aiming a fairly young market
Task
B1: Do you think then we should really consider voice recognitionTask
Auto-F.
Turn
B2: What do you think Craig
Task
Turn
C1: Well did you not say it was the adults that we’re going for
Auto-F.
Turn
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Speech disfluencies
Uh I will be talking to you about two funda-- uh three fundamental ideasutterance
TurnManagement
Time Management
Discourse Structuring
Own Communication Management
Task INFORM INFORM
TAKE
STAL
KEEP
STAL
INTERACTION STRUCTURING
SELF-CORRECTIONSUBSTITUTION
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Multimodal: example
D1: wording: What’s teletext?
gaze: averted personA personB
eyes: narrow
posture: working position
Auto-FB: Neg. understanding
Turn M.Turn assign to A
B1:wording: Um It’s British thing
gaze: averted personD personA personD
eyes: widen
lips: random movements
posture: bowing working position
Auto-FB: Pos. attention
Turn M. Turn take Turn keep
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Example
regardless we're we're aiming for the under sixty five person A person D person A personC personA
table
person A
B:
wording: But thgaze: person D
posture: working position
I thinkperson A
A:wording:
gaze: person B
head
posture working position
short multiple nods(5) table
bowing
Under sixty five okay That’s a good start
short multiple nods(4)
D:Wording:
Gaze: person A
Head:
Posture: working position
person B
short multiple nods(5)
C: Wording:
Gaze: person D
Head:
Face:
Posture: working position
person A person B
Yep
long nods(2)
blinking
short single nod
A believes that B wants to have the turn
A believes that B wants to continues as a speaker
D believes that B wants to continues as a speaker
A believes that she understood the B’s utterance correctly
A reports about the positive evaluation of B’s utterance and offers for further debate
C believes that B believes that p and C believes that p is true
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Relations
• for understanding discourse, insufficient to consider the content of its segments in isolation
• not a single ”coherence” dimension, rather• interplay between several structures, e.g.
– semantic/ inter-propositional/ ideational/ content level/ information-level;
– pragmatic/ intentional/cognitive/ speech-act; – presentational/ structural/textual.
See Hovy et al. (1995)
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Relations
• Functional and feedback dependence relations
– Relation between initial and responsive dialogue acts (“backward- and forward-looking functions” (DAMSL)
– All responsive dialogue acts have an ‘antecedent’
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Type A: semantic content is co-determined by that of their functional antecedent due to their communicative functions (functional dependence relation; ISO 24617-2)
Example:A1: I’m expecting Jan, Alex, Claudia, and David, and maybe Olga
and Andrei to come.B1: Do you know who’s coming tonight?B2: Which of the project members do you think will be there?
A functional dependence relation exists between a dialogue act DA1 and one or more previous dialogue acts {DAN} if, due to the responsive communicative function of DA1, the determination of its semantic content requires the semantic content of {DAN}.
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Type B: responsive dialogue acts that provide or elicit information about the (perceived) success in processing a segment of communicative behaviour earlier in the dialogue
G1: you are going F2: mmhm G2: straight north
A feedback dependence relation is a relation between a feedback act and the stretch of communicative behaviour whose processing the act provides or elicits information about.
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• Rhetorical relations– have been proposed as an explanation for the
construction of coherence in discourse– a range of taxonomies (e.g. Mann and Thompson
(1988), forming the core of Rhetorical Structure Theory)
– Hovy and Maier (1995) studied approximately 30 alternative proposals and fused the various taxonomies into more than 400 relations. They proposed a hierarchical taxonomy of approximately 70 relations.
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Rhetorical relations do not necessarily relate the semantic contents of dialogue acts, but may also relate the dialogue acts (semantic content + communicative function)
A1: Where would you physically position the buttons?A2: I think that has some impact on many things
B1: I’m afraid we have no time for that.B2: We’re supposed to finish this before twelve.
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Qualifiers
A communicative function qualifier:• is an additional element in the description
of a dialogue act• does not change but specifies in more
detail the way in which the dialogue act changes the addressee’s information state
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Semantics of qualifiers: examples
(1) A: The new student is brilliant and imaginative.
B: He’s imaginative.
(2) A: Would you like to have some coffee?1. B: I’m not sure I want any.2. B: Maybe later?3. B: Yes, I definitely need some.4. B: Yes, please, if you don’t mind
to bring it for me.5. B: Coffee? At midnight?
Partial Agreement
Uncertain Offer Accept
Certain Offer Accept
Conditional Offer Accept
Surprise
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Qualifiers: summaryqualifier attribute qualifier values communicative function category
modality uncertain,certain information-providing functions
conditionality conditional, unconditional action-discussion functions
sentiment Angry, happy, surprised, ...
Positive/negative
information-providing functions;feedback functions
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MetamodelDialogue
Turn unit
Functional segment
Dialogue actparticipant
Segment group
Dialogue act group
Communicative functionSemantic content
functional dep. relation
sender
2..N
0..N
2..N
2..N1..N
1..1 1..1
1..1
addressee1..N
others0..N0..N
0..N
feedback dep. relation
0..N
inter-propositionalrelation
0..N
rhetorical relation
0..N
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Homework
• Annotate dialogue (TRAINS_dialogue.xls) using ISO 24617-2/DIT++ taxonomy http://dit.uvt.nl/
• For tutorial (07.07.2015) download Weka toolhttp://www.cs.waikato.ac.nz/ml/weka/
downloading.html
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Dialogue act recognition
• Communicative function recognition
• Multidimensional segmentation and classification, incl. algorithms
• Features selection and extraction form multiple sources
• Evaluation
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Features
• dialogue history: functional tags of the 10 previous turns;• timing: token duration and floor-transfer offset computed
in milliseconds; • Prosody: minimum, maximum, mean, and standard
deviation for pitch (F0 in Hz), energy (RMS), voicing (fraction of locally unvoiced frames and number of voice breaks) and speaking rate (number of syllables per second);
• lexical information: bow, bi- and trigram • In total, 1,668 features are used for the AMI data.
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Features: AMI data
Temporal info
Prosodic info, e.g. 46 festures Participants info
ASR output – bow, n-grams, etc., e.g. 1680
featuresPrevious DAs,
e.g. 10
start end dura-tion
Pitchmean
intensity Voice breaks
speaker Pr_speaker
Addressee
token POS Dialogue history
Predicted label
50.42 50.99 0.57 206.964 49.792081 B _ group okay aff _ opening
53.56 53.96 0.4 326.863 47.581621 B B group right jj opening structuring
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One- vs. Multidimensional segmentation
Classification task Frequency(in %)
BL Single segmentation
Multidimensional segmentation
Task 31.8 32.7 66.1 72.8*Auto-Feedback 20.5. 43.2 80.4 86.3 ∗Allo-Feedback 0.7 70.2 98.4 99.6Turn Management 50.2 34.2 88.3 90.0Time Management 26.7 43.7 72.6 82.1*Discourse Structuring 2.8 41.2 74.3 74.3Contact Management 0.1 59.9 97.3 97.3Own Communication Management 10.3 36.5 85.9 87.1Partner Communication Management 0.3 49.5 64.5 64.5Social Obligation Management 0.5 34.5 93.2 93.3
∗ significant at p < .05, one-tailed z-test.
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Precision, recall, f-score
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Classifiers
• Statistical e.g. Naive Bayes, Bayesian Nets, SVM, CRF, etc.
• Rule Inducers: Ripper• k-NN classifiers• Etc.
• Cross-validation/ stratified cross-validation
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Joint segmentation and classification
• In fact, there is no segmentation independently from classification
• human language understander does not wait trying to understand what he is reading/hearing until he has come to the end of the sentence
• evidence that human understanders construct syntactic, semantic, and pragmatic hypotheses on the fly
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Data encoding
To each token communicative function tag(-s) is
assigned
+
Boundary prefix: token starts a segment (B),
is inside a segment (I), ends a segment (E), is
outside a segment (O), or forms a functional
segment on its own (BE)
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Experiments: data encoding
Speaker Token Task Auto-F. Allo-F. TurnM. TimeM.
ContactM.
DS OCM PCM SOM
B it B:inf O O O O O O O O O
B has I:inf O O O O O O O O O
B to I:inf O O O O O O O O O
B look I:inf O O O O O O O O O
B you O O B:check O O O O O O O
B know O O E:check O O O O O O O
B cool I:inf O O O O O O O O O
D mmmhm O BE:positive O O O O O O O O
B and I:inf O O BE:t_keep O O O O O O
B gimmicky E:inf O O O O O O O O O
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Evaluation metrics
• error metric: combined DERsc error metric to evaluate joint segmentation (s) and classification (c):
tokens with wrong boundaries and/or function class total number of tokens
• performance metric: F-score (balance between precision and recall)
X 100DERsc =
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Dialogue act recognition: AMI data (local classifiers)
BL Bayes Net Ripper
Dimension F1 DERsc F1 DERsc F1 DERsc
Task 32.7 51.2 52.1 48.7 66.7 42.6Auto-Feedback 43.2 84.4 62.7 33.9 60.1 45.6
Allo-Feedback 70.2 59.5 73.7 35.1 71.3 49.1
Turn Management 34.2 95.2 57.0 58.4 54.3 81.3
Time Management 43.7 96.5 64.5 46.1 61.4 53.1
Discourse Structuring 41.2 35.1 72.7 19.9 50.2 30.9
Contact Management 59.9 53.2 71.4 49.9 83.3 37.2
Own Communication Management 36.5 87.9 68.3 51.3 58.3 76.8
Partner Communication Management 49.5 59.0 58.5 45.5 51.4 58.7
Social Obligation Management 34.5 47.5 86.5 35.9 83.3 44.3
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Global classification• Adaptive training (Van den Bosch, 1997): 5 previous and 5 future local predictions
Bayes Net Ripper
Classification task F1 DERsc F1 DERsc
Task 82.6 9.5 86.1 8.3Auto-Feedback 81.9 1.9 95.1 0.6Allo-Feedback 96.3 0.6 95.7 0.5Turn Management 85.7 1.5 81.5 1.6Time Management 90.4 2.4 93.4 1.7Discourse Structuring 82.1 1.7 78.3 1.8Contact Management 87.9 1.2 94.3 0.6Own Communication Management 78.4 2.2 81.6 2.0Partner Communication Management 71.8 2.4 70.0 4.6Social Obligation Management 98.6 0.4 98.6 0.5
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Exercise
• Open Weka Explorer• Unpack ami_new_final.rar• Open ami_new_final.arff• Select classifier and run training experiments• Report results
Dialogue contribution processing
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Update operators
control
CL2 CL3
features wording syntax prosody nonverbal .. previous utterances features
utterance
CL1
DA2 DA3
Dialogue act recognition/generation DA1
Features selection/clustering/classification
Context model Cognitive context Semantic context Social context Perceptual context Linguistic context Context Manager
Dialogue Act Agents Task-Agent AutoFB-Agent AlloFB-Agent TurnM-Agent TimeM-Agent etc.
Candidate DAs