Transcript Discourse Markers - University of Chicago

Discourse Markers
Discourse & Dialogue
CS 35900
November 25, 2006
Agenda
• Definition
• Motivation
• Understanding Discourse Markers in
Human-Human Dialogue
• Using Discourse Markers in HCI
– Structuring instructions
– Improving recognition
– Recognizing conversational and dialogue acts
Discourse Markers
• “Cue”/”Clue” phrases
– 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
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>...
Why Discourse Markers?
• Prevalent:
– Begin 65% human-human task utterances
• 44% excluding acknowledgments
• 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?
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
Levels of Contribution
• Wide scope -> less communicative force
– Narrow scope -> more communicative force
• More markers -> decrease individual impact
– Clearer discourse structure -> fewer DMs
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
Discourse Markers & Coherence
• Establish coherence by
– Locate utterance on “plane of talk”
• Exchange, action, idea, participation frame, info
status, etc
– Turn-taking, task step, semantics, attitude, etc
– Index local context reference for interpretation
• Establish direction of relation to surrounding utts
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.
Generating Discourse Markers
• Integrate intentional & informational
– Grosz & Sidner; Mann & Thompson
– Identify nuclear DSP and contributing relations
• Pairwise relations of rhetorical types (intent)
– E.g. concession:nucleus
• Relations based on task/domain (inform)
– E.g. step:prev-result
– Interpret cues wrt discourse structure/relations
• “since”: contributor:nucleus;”because”:nucleus:contributor
• No duplication of cues within embedded relations
– Duplicate in sequence
Characterizing Discourse Markers
• Problem: Ambiguity
– Discourse use vs sentential use
• E.g. “now”: Topic initiation vs temporal meaning
– Overall: 1/3 ambiguous; coord conj: ½
• Disambiguation:
– Prosody: 84% (non-conj: 93%)
• DM: own intermediate phrase; or first, no accent
• Sentence: no separation, H* or complex accent
– Text: 89%
• DM: preceding punctuation
– POS weaker cue
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”
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
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
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