1. Turn-Taking, Grounding and Speaker Segmentation
Julia Hirschberg
LSA07 353
11/17/2018

2. Today Turn-taking behaviors in human-human conversation
Conversational Analysis accounts
Task/circumstance/individual dependencies
Linguistic/cultural differences
Grounding analyses
Diarization: Automatic Turn Identification
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3. Turn-taking Behavior
How do speakers know when it is appropriate to contribute to a conversation?
Conversational Analysis Theory: 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
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4. Children learn turn taking within first 2 years (Stern ’74)
Children liked by their peers are more skilled (Black & Hazen ’90)
General individual differences
Shy people pause longer and speak less and less often (Pilkonis ’77)
Schizophrenics, neurotics, depressed people less skilled in turn-taking
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5. Expectations of What to Say 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
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6. Email Service encounters Meetings News broadcasts
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.
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7. 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
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8. 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
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9. 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
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10. But where is the intent? Purpose?
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11. Grounding Approaches to Conversational Modeling
Conversation is a joint process through which S and H are constantly negotiating a common ground (Stalnaker ’78, Clark ’96 inter alia)
Cf mutual belief
Principle of Closure: agents performing an action require evidence that they have succeeded (Norman ’88)…or not
Clark & Schaeffer ’89
Presentation (by S) and Acceptance (by H) via
Continued attention, relevant next contribution, acknowledgement/assessment, demonstration, display
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12. S: John Stewart is my favorite comedian
H: {continued attention}
H: The Daily Show is not to miss {rel next contrib}
H: Mhmm {acknowledgement}
H: He’s the funniest person you know {demonstr}
H: Your favorite comedian {display}
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13. Importance in SDS
Turn-taking models and theories of grounding of considerable potential use in SDS
What is the User likely to say next and when?
How can we be sure what the User has said and its relationship to what s/he believes to be true?
What type of response does s/he expect the system to make? When?
Obstacles for practical use:
What cues signal when it is appropriate to speak?
How do we negotiate a common system/user ground?
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14. When Is It Appropriate to Speak? (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
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15. Beattie’s classification scheme:
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
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16. 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
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17. Results
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
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18. 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
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19. Automatic Speaker Identification/Segmentation
Diarization: Segmentation of audio corpora (Broadcast News, meetings, telephone conversations) into speaker segments
Speaker turns
Speaker identification
Speech and music
Speaker segmentation
Initial segmentation
Segment clustering based on acoustic features
State-of-the-art: 8.47% error
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20. <DOCNO> CNN19980104.1130.0000 </DOCNO>
<DOCTYPE> MISCELLANEOUS TEXT (automatic initial) </DOCTYPE>
<DATE_TIME> 01/04/ :30:00.00 </DATE_TIME>
<BODY>
<TEXT>
</TEXT>
</BODY>
<END_TIME> 01/04/ :30:34.71 </END_TIME>
</DOC>
<DOCNO> CNN </DOCNO>
<DOCTYPE> NEWS STORY </DOCTYPE>
<DATE_TIME> 01/04/ :30:34.71 </DATE_TIME>
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.
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21. 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.
foir people have been taken to hospitals.
one firefighter was injured and treated on the scene.
</TEXT>
</BODY>
<END_TIME> 01/04/ :31:31.00 </END_TIME>
</DOC>
<DOC>
<DOCNO> CNN </DOCNO>
<DOCTYPE> NEWS STORY </DOCTYPE>
<DATE_TIME> 01/04/ :31:31.00 </DATE_TIME>
<BODY>
<TEXT>
authorities in brooklyn, new york, say an explosion at a tire company has
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22. 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/ :31:48.11 </END_TIME>
</DOC>
<DOC>
<DOCNO> CNN </DOCNO>
<DOCTYPE> NEWS STORY </DOCTYPE>
<DATE_TIME> 01/04/ :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.
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23. 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.
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24. 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
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25. Online Turn Identification for SDS
Push-to-talk systems
Silence detection
Speech detection
Barge-in
Need more ‘natural’ turn-taking support
When are users ready to be interrupted?
When do they want to keep the floor?
When do they expect the system to backchannel?
How can we indicate when the system has finished its turn?
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26. Conclusions
Turn-taking models and theories of grounding of considerable potential use in SDS
What is the User likely to say next and when?
How can we be sure what the User has said and its relationship to what s/he believes to be true?
What type of response does s/he expect the system to make? When?
Obstacles for practical use:
What cues signal when it is appropriate to speak?
How do we negotiate a common system/user ground?
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27. Next Class
We know a few things we need to accomplish and a bit about the difficulties….
What tools do we have to use in tackling the problems?
Components of SDS:
Automatic Speech Recognition
Text-to-Speech
Readings: J&M 22.2
11/17/2018