1. Turn-taking and Disfluencies
Julia Hirschberg
CS 6998
11/29/2018

2. Today Turn-taking behaviors Conversational Analysis
Importance in real systems
Disfluencies
How to model? Detect?
Role in human-human interaction
Importance in real systems?
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3. Turn-taking Expected patterns of behavior Deviation is significant
How do we find the patterns?
Ordinary conversation
Telephone talk
Meetings ?
Who looks for these? (Ilana)
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4. Telephone openings, closings Broadcasts
Terminology
Adjacency pairs
Preference
Pre-sequence
Repair
Examples:
Telephone openings, closings
Broadcasts
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5. Could this be useful when we build SDS?
What do we expect to hear?
What should we produce?
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6. Disfluencies and Self-Repairs
Are these just ‘noise’?
For people (Heba)
For parsers
For speech recognizers
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7. Hindle ’83: Finding the Edit Signal
If we have it, can we ‘repair’ the self-repair automatically?
Builds a correcting parser, Fidditch, for spontaneous speech
Given a string with an edit signal marked, produces a ‘repaired’ version
I was * I am really annoyed
If X1 * X2 are similar linguistic elements separated by an edit signal, replace X1 w/X2
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8. What does it mean to be the same
Same surface string
Well if they’d * if they’d…
Same category
I was just that * the kind of guy…
Same constituent
I think that you get * it’s more strict in Catholic schools
Restarts are completely different…
I just think * Do you want something to eat?
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9. Bear et al ’92: Detecting and Correcting Self-Repairs
Use multiple knowledge sources but not edit signal
Lexical pattern matching
Parsing failure + pattern matching + re-parsing
Acoustic information: pause, peak F0,
Cue words: well, no
Fragments
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10. But…is there an edit signal?
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11. Does it identify self-repairs reliably?
CART prediction: 86% precision, 91% recall
Duration of interval, presence of fragment, pause filler, p.o.s., lexical matching across DI
Are there edit signals?
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12. Next Week
11/29/2018