Discourse Markers
description
Transcript of Discourse Markers
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Discourse Markers
Discourse & Dialogue
CS 35900
November 25, 2006
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Agenda
• Definition• Motivation• Understanding Discourse Markers in Human-
Human Dialogue• Using Discourse Markers in HCI
– Structuring instructions– Improving recognition– Recognizing conversational and dialogue acts
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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
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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>...
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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?
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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
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Levels of Contribution
• Wide scope -> less communicative force– Narrow scope -> more communicative force
• More markers -> decrease individual impact– Clearer discourse structure -> fewer DMs
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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
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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
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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.
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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
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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
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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”
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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
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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
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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