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This publication explores turn-taking rules and diarization processes in conversational interactions, focusing on how speakers allocate and transition between turns. It delves into the system's mechanisms governing speaker changes, overlapping speech patterns, and techniques for selecting the next speaker. Through examples and analyses of various conversational scenarios, the text sheds light on the nuanced intricacies of discourse construction and the expectations associated with conversational behaviors.
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Turn-Taking, Grounding and Diarization Julia Hirschberg LSA07 353
Rules Governing Turn Construction 1. For any turn, at a transition-relevant place: • If “current speaker selects next” then the person selected is obligated to take the next turn. • If not, self-selection may be instituted. • Or, the current speaker may continue unless someone self-selects. 2. If 1c occurs, then rules a-c reapply at the next transition-relevant place
The System Accounts for: • Speaker change • One party talking majority of the time • Occcurrences of more than one speaker at a time are common but brief
Types of Overlap • Accounted for by rule 1b (self-selection): Competing for next turn. Lil: Bertha’s lost, on our scale, about fourteen pounds. Damora: Oh[::no::, Jean: [Twelve pounds I think wasn’t it = Daisy: [Can you believe it? Lil: [Twelve pounds on the Weight Watcher’s scale.
Types of Overlap (cont…) • Assume you know how the speaker will finish. A: Well if you knew my argument why did you bother to a:[sk. B: [Because I’d like to defend my argument. • The speaker added optional elements that can go after completion. A: Uh you been down here before [havenche, B: [Yeh.
Turn Order/Size • Turn Order • Not fixed yet it’s not random • Bias: Speaker before the current speaker is selected as the next speaker • Turn Size • Not fixed • Why? • Because of unit types (single-word turns, single phrase turns, etc.) • Because of rule 1C (current speaker can continue) the speaker can produce more than one unit type
More on Turns • The length and content of conversations are not specified in advance • Anyone can be the next speaker • Number of parties can vary. • With 4 you can have multiple conversations • Turns begin at “possible completion points” • Repairs exist for errors: • Who me? • Excuse me?
Continuous or Discontinuous • Talk can be continuous or discontinuous • Continuous = minimum gap or overlap • Discontinuous = a current speaker has stopped and no speaker starts, and non-talk is a lapse. J: Oh I could drive if you want me to. C: Well no I’ll drive (I don’ m//in’). J: hhh. (1.0) J: I meant to offah. (16.0) J: Those shoes look nice when you keep on putting stuff on ‘em. C: Yeah I ‘ave to get another can cuz cuz it ran out….
Turn Allocation Techniques: Select Next Speaker 1. “Type of Sequence” parts. (Adjacency pairs). Examples: • Complaint/denial Ken: Hey yuh took my chair by the way an’t I don’t think that was very nice. Al: I didn’ take yer chair, it’s my chair. • Compliment/rejection A: I’m glad I have you for a friend. B: That’s because you don’t have any others.
Turn Allocation Techniques: Select Next Speaker (cont…) 2. Repeat parts of prior utterance with a question intonation or one word question. Ben: They gotta – a garage sale Lori: Where. Ben: On Third Avenue.
Turn Allocation Techniques: Select Next Speaker (cont…) 3. Tag question • You know? Don’t you agree? 4. Introduce social identities • Two couples speaking. An invitation is made by a speaker to go to the movies. The next speaker should be a member of the other couple.
Turn Allocation Techniques: Self-Selection 1. Starting First 2. “Second Starters” R: Hey::, the place looks different F: Yeah::hh. K: Ya have to see all ou[r new-* D: [It does?* R: Oh yeah
Consequences of the Model • Motivation for listening to all utterances in a conversation • To see if you are the next speaker • If you want to speak, make sure no one else was selected to speak • When a new speaker is selected, the speaker has to perform the second part of the adjacency pair. • Shows he understood the prior turn’s talk as the first part
Today • Turn-taking behaviors in human-human conversation • Task/circumstance dependencies • Conversational Analysis • Linguistic/cultural differences • How do we take and give up turns? • Diarization: Automatic Turn Segmentation
Turn-taking Behavior • Dialogue characterized by turn-taking • How do speakers know what to say and when to say it? • Conversational partners expect certain patterns of behavior in normal conversation Pat: You got an A? That’s great! Chris: Yeah, I’m really smart you know. Chris: Well, I was just lucky I happened to read the chapter on dialogue systems right before the test. Otherwise I never would have squeaked through. • General patterns in ordinary conversation • Deviation is significant
Children learn turn taking within first 2 years (Stern ’74) • General individual differences • Shy people pause longer and speak less and less often (Pilkonis ’77) • Schizophrenics, neurotics, depressed people less skilled in turn-taking
Expectations of What to Say May Depend on Task at Hand • Telephone • Openings Pat: Hello? Chris: Hi, Pat. It’s Chris. Pat: Hi! • Closings (6-turn) Chris: Well, I just wanted to see how you were doing Pat: Thanks for calling. We'll have to have lunch sometime Chris: I'd like to Pat: Okay Chris: Okay Pat: See you Chris: Yeah, see you
Email Pat: “Hi, can we switch lunch to 12:30? I’m running late.” Chris: “Sure. 12:30.” Pat: “Great. See you.” • Service encounters Clerk: Good morning. Is there something I can help you with? Pat: Hi. Yeah. I wonder if you could show me…. • Meetings Boss: Today I want to focus on next year’s goal statements. Chris, could you report please…. Chris: … Boss: Pat, now let’s hear from you… Pat: … • News broadcasts Anchor: …Chris Smith reports from Rome now on the upcoming conclave. Chris? Reporter: Thanks, Pat….. And now back to Pat Jones in New York.
Today • Turn-taking behaviors in human-human conversation • Task/circumstance dependencies • Conversational Analysis • Linguistic/cultural differences • How do we take and give up turns? • Diarization: Automatic Turn Segmentation
Conversational Analysis (Sacks et al ’74) • Can we characterize expectations of ‘what to say’ more generally? • ‘Rules’ of turn-taking • If, during this turn the current speaker has selected A as the next speaker, then A must speak next • If the current speaker does not select the next speaker, any other speaker may take the next turn • If no one else takes the next turn, the current speaker may take the next turn • Rules Apply at Transition Relevant Places (TRPs) where something allows speaker changes to occur
Where Can Speaker Shifts Occur • Adjacency pairs • Question/answer • Greeting/greeting • Compliment/downplayer • Dispreferred responses • Silence • ‘No’ to a simple request without explanation • Changing the topic abruptly without transition • Important for Spoken Dialogue Systems
Today • Turn-taking behaviors in human-human conversation • Task/circumstance dependencies • Conversational Analysis • Linguistic/cultural differences • How do we take and give up turns? • Diarization: Automatic Turn Segmentation
Cultural Differences in Turn-Taking • Chinese telephone conversations • Openings (Zhu ’04) • Mandarin vs. British • Identification differences • British self-report • Chinese callees ask the caller • Closings (Sun ’05) • 39 female-female telephone conversations • Closings initiated through matter-of-fact statement of intention to end conversation • Verbalized thanking occurs except in mother/daughter closings – not the standard English model • Finnish business calls (Halmari ’93) vs. American • Americans get right to the point • Finns chat
Today • Turn-taking behaviors in human-human conversation • Task/circumstance dependencies • Conversational Analysis • Linguistic/cultural differences • How do we take and give up turns? • Diarization: Automatic Turn Segmentation
Individual Differences: British Politicians (Beattie ’82) • Data: 25m televised interviews before 1979 British General election • Margaret Thatcher (Tory leader): the Iron Lady • Jim Callaghan (Prime Minister): Sunny Jim • Who interrupts? • Less intelligent, highly neurotic, extroverted • Men interrupt women • Interruptions may indicate • Desire for dominance • Desire for social approval • Conveyance of ‘joint enthusiasm’, heightened involvement
Method: • Identify spkr 2 attempts to take the turn • Smooth switches: no simultaneous speech, spkr 1’s utterance complete, turn to spkr 2 • Simple interruptions: simultaneous speech, spkr 1 doesn’t complete utterance, turn to spkr 2 • Overlap: simultaneous speech, spkr 1 completes utterance, turn to spkr 2 • Butting-in: simultaneous speech but no change of turn, spkr 1 keeps the turn • Silent interruption: spkr 1’s utterance incomplete, no simultaneous speech, turn to spkr 2
Analyze acoustic/prosodic and gestural information • Turn-yielding behavior • Pauses • Speaking rate slows • Drawl at end of clause • Drop in pitch or loudness • Completion of syntactic clause • Gesture of termination • Attempt suppression signals • Filled pauses • Gestures
Results • Mrs. Thatcher interrupted almost twice as often as she interrupts interviewer (19/10)– unlike Callaghan (14/23) • Thatcher: Starts slow and gets faster, few FPs (4) • Callaghan: starts fast and gets slower, many FPs (22) • Public perception: Thatcher is domineering in interviews and Callaghan is a ‘nice guy’ • But Thatcher does not dominate • Why is Thatcher interrupted? • Interruptions come at end of syntactic clause when drawl on stressed syllable in clause and falling intonation
No suppression signals • Why does she do this? • Speech training before election? • Why is she still perceived as domineering? • When interrupted she doesn’t cede the floor despite lengthy stretches of simultaneous speech
Today • Turn-taking behaviors in human-human conversation • Task/circumstance dependencies • Conversational Analysis • Linguistic/cultural differences • How do we take and give up turns? • Diarization: Automatic Turn Segmentation
Diarization: Automatic Speaker Identification/Segmentation • Segment audio corpora (Broadcast News, meetings, telephone conversations) into speaker segments • Speaker segmentation • Speaker identification • Speech and music • Speaker segmentation (Diarization) • Initial segmentation • Segment clustering based on acoustic features • State-of-the-art: 8.47% error
Speaker identification • Linguistic information to identify speaker types and speaker names (LIMSI ’04) • Templates (“<name> has this report from <location>”) • Results: 10.9% error on test set • But only 10% of segments contain relevant patterns • Estimate 25% error on broadcast news if segmentation and clustering is done to id all of each speaker’s segments
<DOC> <DOCNO> CNN19980104.1130.0000 </DOCNO> <DOCTYPE> MISCELLANEOUS TEXT (automatic initial) </DOCTYPE> <DATE_TIME> 01/04/1998 11:30:00.00 </DATE_TIME> <BODY> <TEXT> </TEXT> </BODY> <END_TIME> 01/04/1998 11:30:34.71 </END_TIME> </DOC> <DOC> <DOCNO> CNN19980104.1130.0034 </DOCNO> <DOCTYPE> NEWS STORY </DOCTYPE> <DATE_TIME> 01/04/1998 11:30:34.71 </DATE_TIME> <BODY> <TEXT> in northern kentucky are forcing 3,000 people in two states to flee their homes. the fire started early this morning at the cargill company plant in maysville near the ohio river. authorities have been going door-to-door advising people in kentucky and ohio to take shelter in area high schools. the fire is in a building where several fertilizers and chemicals are stored.
officials say all they can do is let the fire burn itself out, because spraying water on the flames would be too dangerous. <TURN> at the current time, our only way of getting it under control is to stay away from it. we've backed everyone off from the fire by about a mile and a quarter and evacuated homes in that radius and the chief threat at this point is a very small risk of a very large explosion caused by 400 tons of ammonia nitrate stored in the building. <TURN> foir people have been taken to hospitals. one firefighter was injured and treated on the scene. </TEXT> </BODY> <END_TIME> 01/04/1998 11:31:31.00 </END_TIME> </DOC> <DOC> <DOCNO> CNN19980104.1130.0091 </DOCNO> <DOCTYPE> NEWS STORY </DOCTYPE> <DATE_TIME> 01/04/1998 11:31:31.00 </DATE_TIME> <BODY> <TEXT> authorities in brooklyn, new york, say an explosion at a tire company has
caused at least three buildings to collapse. it set off a four-alarm fire, which has been contained. officials tell cnn one person was injured. investigators have not determined the cause of the incident. </TEXT> </BODY> <END_TIME> 01/04/1998 11:31:48.11 </END_TIME> </DOC> <DOC> <DOCNO> CNN19980104.1130.0108 </DOCNO> <DOCTYPE> NEWS STORY </DOCTYPE> <DATE_TIME> 01/04/1998 11:31:48.11 </DATE_TIME> <BODY> <TEXT> unexpected weather conditions are the rule across much of the united states this weekend. angela astore reports. <TURN> <ANNOTATION> Reporter: </ANNOTATION> it was a nice day to play along the beach -- spend a few hours fishing -- or get in a game of golf -- not uncommon -- unless it's january in chicago. record high temperatures were set yesterday from minnesota to massachusetts. warm air drawn northward from the gulf of mexico was behind the rise in the mercury.
it was a different scene in the northwest, where snow is the story. but the winter weather didn't stop this man from getting in some warmer pursuits. and he wasn't bothered by the fact that he couldn't see where his golf balls landed. <TURN> it's not really where it's going to land that's important at this point while you are learning. once you've learned, then it is. we'll worry about that when the snow clears. right now, it's probably better that i don't see where they land.
Next Class • Components of SDS: • Automatic Speech Recognition • Text-to-Speech • Natural Language Understanding