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