1. Discourse & Dialogue CS 359 November 13, 2001
Discourse Markers
Discourse & Dialogue
CS 359
November 13, 2001

2. Business Final Projects due: December 3, 2001
Final project issues: Let me know...
Data: What materials will you use?
How will you get them?
Processing:
Tools: Analysis, synthesis,..?

3. Agenda Definition Motivation
Understanding Discourse Markers in Human-Human Dialogue
Using Discourse Markers in HCI
Structuring instructions
Improving recognition
Recognizing conversational and dialogue acts

4. Discourse Markers “Cue”/’Clue” phrases Signal discourse structure
E.g.“By the way”, “so”, “now”, “anyway”
Signal discourse structure
E.g. asides, new topics, returns
Signal relations between segments
Cohesion, continuation, contrast, etc
Appropriate use clarifies dialogue
Misuse causes confusion

5. Lost in the Mail (Application)
U: Read old messages.
S:Skipping to first old message. Message 1 from Shaw Wen Yang, Subject: Question
U: Read it to me.
S: Call me about the tool, shaw x22630
U:Send a reply.
S:Preparing message to shaw. Do you want to include the current message?
U: Yes
S:Begin recording after the tone……Say cancel, send or review.
U: Send
S: Message sent.
U: <silence>….<touch tones>...

6. Why Discourse Markers? Prevalent:
Begin 65?% human-human task utterances
441% excluding ackonlegdments
Related to discourse meaning/structure
How do linguistic features of DMs interact with discourse properties to create function?
What is the scope?
At what level is relationship marked?
How do meanings contribute to function?

7. Discourse Relations Markers apply on different planes of talk
exchange, action, idea, participation framework, information status
E.g. ‘oh’: primary: info state; 2nd: action, participation
Semantics and syntax contribute to role of DM
E.g. “so” -> result
Mark or disambiguate relations
Don’t create relations

8. Levels of Contribution
Wide scope -> less communicative force
Narrow scope -> more communicative force
More markers -> decrease individual impact
Clearer discourse structure -> fewer DMs

9. Indexical Relations Utterance situated with respect to
Speaker, hearer, time, place
Discourse markers related to context
Proximal (near) vs distal (far) relations
Linkage to preceding/following utterance
preceding - “oh” - proximal; “well”: link pre & post
Speaker - proximal =“oh”; hearer- distal

10. Discourse Markers & Coherence
Establish coherence by
Locate utterance on plane of talk
action, idea, participation frame, info status, etc
Index local context reference for interpretation
Establish direction of relation to surrounding utts

11. A Solution U: Read old messages.
S:Skipping to first old message. Message 1 from Shaw Wen Yang, Subject: Question
U: Read it to me.
S: Call me about the tool, shaw x22630
U:Send a reply.
S:Preparing message to shaw. Do you want to include the current message?
U: Yes
S:Begin recording after the tone……Say cancel, send or review.
U: Send
S: Message sent. What now?
U: Next message.

12. Generating Discourse Markers
Integrate intentional & informational
Grosz & Sidner; Mann & Thompson
Identify core DSP and contributing relations
Pairwise relations of rhetorical types (intent)
E.g. concession:core
Relations based on task/domain (inform)
E.g. step:prev-result
Interpret cues wrt discourse structure/relations
“since”: contributor:core;”because”:core:contributor
No duplication of cues within embedded relations
Duplicate in sequence

13. Improving Recognition
Discourse markers as special case of POS tagging
POS = part of speech
E.g. noun, verb, conjunction, etc
Discourse marker POS:
Acknowledgment: “okay”; “uh-huh|’
Interjection DM: “oh”,””well”
Conjunction DM: “and”,”but”
Adverb DM: “now”,”then”

14. Recognizing Markers Build joint model of word+POS recognition
Expand ASR model
Build decision trees to identify equivalences
Handle sparseness
Build binary classification trees
Successive merging with least information loss
Apply to POS and word+POS pairs
Cluster unambiguously
Joint modeling improves POS tagging
Additional discourse features further improve
Boundary tones, repairs, silence

15. Discourse Markers & Structure
Discourse markers correlated with conversational moves
E.g. “so”- summarize; “well” - dissent
Discourse markers NOT correlated with subsequent speech acts
Correlated with PRIOR talk
Previous turn initiates adjacency pair -> no DM
Previous turn concludes adjacency pair -> DM
Clear expectation: no DM; unclear -> DM

16. Recognizing Dialogue Acts
Understand speaker’s intention
“Dialogue act”: SUGGEST, ACCEPT,…
Recognize automatically
More than just discourse markers
~60% accuracy common DM alone
Identify additional dialogue act cues
Potential discourse cues: e.g “see you”
Domain cues: Wednesday -> SUGGEST

17. Learning Dialogue Act Tags
Transformation-based learning (Brill 1995)
Supervised
Select rule with highest improvemen score
Add rules until improvement no longer exceeds threshold
Produce rule sequence -> increasingly specific
Identify substrings which decrease entropy
Train multiple taggers
Boost by emphasizing misclassified
Use voting as indicator of confidence
Accuracy ~75% with potential & domain cues

18. Discourse Markers Short cue word, phrases that signal
relation of utterance to its context
locate utterance in the “plane” of talk
Important role in disambiguating meanings
Signal shift in topic
Signal changes in footing
Key in loosely organized contexts