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Variation in speech tempo:
Capt. Kirk, Mr. Spock, and all of us in between
Tyler Schnoebelen
Stanford University
Goals
• The social meanings of tempo
– Who uses it, how’s it understood?
• Indexical field construction
– New approaches t...
Kendall (2009)
Region
Ethnicity
Gender
Age
Utterance length
Median pause
But we aren’t robots
Social meaning
• Speech rates are not stable by demographic
category
• They vary all over the place
• Conveying and creati...
Accommodation by ethnicity
Psychology, phonetics
Fast tempo in music
Fast
tempo
Happiness
Pleasantness
Activity
Surprise(Potency)
(Anger)
(Fear)
Psychology, phonetics, musicology
Juslin and Laukka (2003)—104 studies of speech, 41 studies of music
Intraspeaker variation
Style
Indexical fields
• Variables aren’t fixed but are located in a
“constellation of ideologically related
meanings” (Eckert 2...
3 steps to an indexical field
1. Statistically significant correlations with fast
speech rate in psychology and linguistic...
Who talks fast?
Unsatisfying?
The structure of indexical fields
• It should be possible to relate items within the field
• And this should allows us to ...
Clustering
• Take the indexical field (41 items)
• Also add “fast-talkers” and “slow-talkers”
• Ask for pair-wise judgment...
Sample of the data
active angry; in a rage anxious
active 2.11 -0.373 -0.156
angry; in a rage -0.433 2.08 -0.0549
anxious ...
Predictions
• The main clusters that emerge will be
connected to two inter-related notions:
– Ideologies of time
– Emotion...
Overwhelmed
Other-oriented
Overwhelming
Authoritative
Persuading
What’s this showing?
• Time and emotional arousal may well underlie
the field
• But a different axis is much more apparent...
Tempo varies
Who
Iasked
who
uses
tempo
at
theoppositeextreme
who?
We’ve got to get Spock to Vulcan!
Tunnel of terror
And some others
William Shatner impersonation
Leonard Nimoy’s Mr. Spock is even
A cue from the Internet
Burstiness
• Variance / (syllables * 0.5)
– Variance gets us dispersion of the data
– The denominator helps us see how spr...
Burstiness and emotionality
• 48 Americans judged the emotional intensity of
228 utterances
– Utterances taken from 8 epis...
Emotional speech in Star Trek is bursty
speech
Better than speech rate
• Among factors tested:
– Burstiness
– Speech rate
– Syllable count
– Interactions among these
• O...
• A better approach is to use a mixed model,
where speaker is a random effect.
– This allows us to see that Kirk and Bones...
Spock in reversal
Bursty, but not emotional
Emotional, but not bursty
Emotionality by Burstiness and
Speaker
AIC BIC logLik deviance REMLdev
341.4 352.7 -166.7 336.7 333.4
Random effects:
Grou...
Summary
• We can move beyond the “who” of variation and into
“how” and “why”
• Indexical fields are a useful conceptual to...
Thank you!
• Collins, S. 1989. Subjective and autonomic responses to Western classical music. Unpublished doctoral dissert...
Appendix
Why look at TV/movies for style?
• Actors are a good source for studies of style since they make vivid the cues
that are m...
Overwhelmed
Other-oriented
Overwhelming
Authoritative
Persuading
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between
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Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between

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Kendall (2009) shows that speech rate correlates to region, ethnicity, gender, and age. Beyond average rates, acceleration and deceleration matter. Psychologists and musicologists link tempo not only to demographic categories, but to emotions and personality-types, too.
An analysis of five Star Trek episodes shows how differences in tempo match differences in characters, from the highly variable tempos of a passionate Captain Kirk to the measured, burst-free speech of the emotionless Mr. Spock. The actors deploy tempo stylistically, creating emotions and personalities that audiences understand.
To calculate evenness and irregularity in tempo, I adapt measures of burstiness that network traffic engineering uses for packets traveling across the Internet: computing the variance in time between syllable nuclei in an utterance, then dividing the variance by 0.5*the number of syllables. The bigger the ratio, the more it is characterized by clusters.
Kirk’s burstiness differs significantly from his crew: at least four times greater than all the others at their burstiest. Everyone’s bursts correlate to emotional “hot spots”—areas of increased involvement (Çetin and Shriberg 2006).
I demonstrate that meanings of tempo are structured by two themes: (i) arousal (“action readiness”) and (ii) ideologies about time. These emerge not just in the Star Trek data but from building
indexical fields for “fast talk” and “slow talk.” In the spirit of Eckert (2008), the fields begin with proven correlations. I also develop a rapid survey methodology—results from 50 participants chart a constellation of ideological meanings that describe who talks fast/slow and when.
This paper differs from most work on social meaning by focusing on a suprasegmental aspect of speech. It also draws upon psychology, anthropology, musicology, and computer science. Its use of performances distills stylistic tempo from reflexive, cognitive effects, offering insights that assist our understanding of how tempo gets used in naturally-occurring speech.

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Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between

  1. 1. Variation in speech tempo: Capt. Kirk, Mr. Spock, and all of us in between Tyler Schnoebelen Stanford University
  2. 2. Goals • The social meanings of tempo – Who uses it, how’s it understood? • Indexical field construction – New approaches to structuring indexical fields • Between fast speech and slow speech: burstiness – A way to measure William Shatner (and everybody else)
  3. 3. Kendall (2009)
  4. 4. Region
  5. 5. Ethnicity
  6. 6. Gender
  7. 7. Age
  8. 8. Utterance length
  9. 9. Median pause
  10. 10. But we aren’t robots
  11. 11. Social meaning • Speech rates are not stable by demographic category • They vary all over the place • Conveying and creating identities and attitudes
  12. 12. Accommodation by ethnicity
  13. 13. Psychology, phonetics
  14. 14. Fast tempo in music Fast tempo Happiness Pleasantness Activity Surprise(Potency) (Anger) (Fear)
  15. 15. Psychology, phonetics, musicology Juslin and Laukka (2003)—104 studies of speech, 41 studies of music
  16. 16. Intraspeaker variation
  17. 17. Style
  18. 18. Indexical fields • Variables aren’t fixed but are located in a “constellation of ideologically related meanings” (Eckert 2008)
  19. 19. 3 steps to an indexical field 1. Statistically significant correlations with fast speech rate in psychology and linguistics literature 2. Corpora (“talk fast” and “are fast talkers”) – Corpus of Contemporary American English – Bing! search results 3. Survey – 50 participants across the US via Mechanical Turk
  20. 20. Who talks fast?
  21. 21. Unsatisfying?
  22. 22. The structure of indexical fields • It should be possible to relate items within the field • And this should allows us to understand constraints • And how different meanings come to attach to different variables • My assumptions: – Indexical fields expand and contract over time – New meanings rely upon what’s already there – “The no teleportation” hypothesis – In principle, sadness and fast talk could come to be related but the path is unlikely
  23. 23. Clustering • Take the indexical field (41 items) • Also add “fast-talkers” and “slow-talkers” • Ask for pair-wise judgments of how much overlap there is between each pair – ie, “New Yorkers” overlap with “Northerners”, but “teachers” don’t overlap with “con-men/hustlers” • 20 judgments for each pair (840 pairs) • 245 Americans surveyed via Amazon Mechanical Turk • Hierarchical clustering based on correlation patterns (but non-hierarchical methods give similar results)
  24. 24. Sample of the data active angry; in a rage anxious active 2.11 -0.373 -0.156 angry; in a rage -0.433 2.08 -0.0549 anxious -0.298 -0.0875 2.08 auctioneers 0.500 -1.331 -0.898
  25. 25. Predictions • The main clusters that emerge will be connected to two inter-related notions: – Ideologies of time – Emotional arousal
  26. 26. Overwhelmed Other-oriented Overwhelming Authoritative Persuading
  27. 27. What’s this showing? • Time and emotional arousal may well underlie the field • But a different axis is much more apparent: – Speaker-orientation vs. listener-orientation • Fast-speech is about time, but are you talking fast for me or for yourself? – There’s a parallel to IN’ vs. ING • Do I take your IN’ as a sign of friendliness or as evidence of laziness?
  28. 28. Tempo varies
  29. 29. Who
  30. 30. Iasked
  31. 31. who
  32. 32. uses
  33. 33. tempo
  34. 34. at
  35. 35. theoppositeextreme
  36. 36. who?
  37. 37. We’ve got to get Spock to Vulcan!
  38. 38. Tunnel of terror
  39. 39. And some others
  40. 40. William Shatner impersonation
  41. 41. Leonard Nimoy’s Mr. Spock is even
  42. 42. A cue from the Internet
  43. 43. Burstiness • Variance / (syllables * 0.5) – Variance gets us dispersion of the data – The denominator helps us see how spread out the data is – The bigger the ratio, the more it is characterized by clusters (“bursts”)
  44. 44. Burstiness and emotionality • 48 Americans judged the emotional intensity of 228 utterances – Utterances taken from 8 episodes, focusing on: • Captain Kirk • Mr. Spock • Lt. Sulu • Dr. (Bones) McCoy – Each utterance judged by 3-5 people – Scores were normalized per judge and then averaged – Top 30, bottom 30 and 63 randomly chosen in between were analyzed for speech rate and burstiness – Restricted to utterances that were at least 5 syllables
  45. 45. Emotional speech in Star Trek is bursty speech
  46. 46. Better than speech rate • Among factors tested: – Burstiness – Speech rate – Syllable count – Interactions among these • Only burstiness is significant (in a simple linear regression model or an ordinary least squares model, p=~0.0125) – But note that the r-squared isn’t all that great: 0.05044
  47. 47. • A better approach is to use a mixed model, where speaker is a random effect. – This allows us to see that Kirk and Bones use burstiness, while Sulu and Spock don’t. • Kirk 0.4371045 • Bones 0.1710811 • Sulu -0.1518260 • Spock -0.4563595 Mixed model
  48. 48. Spock in reversal Bursty, but not emotional Emotional, but not bursty
  49. 49. Emotionality by Burstiness and Speaker AIC BIC logLik deviance REMLdev 341.4 352.7 -166.7 336.7 333.4 Random effects: Groups Name Variance Std.Dev. Speaker (Intercept) 0.21810 0.46701 Residual 0.87055 0.93303 Number of obs: 123, groups: Speaker, 4 Fixed effects: Estimate Std. Error t value (Intercept) -0.07646 0.27625 -0.2768 Burstiness 7.07226 3.07077 2.3031 > pvals.fnc(data.lmer)$fixed Estimate MCMCmean HPD95lower HPD95upper pMCMC Pr(>|t|) (Intercept) -0.0765 -0.0845 -0.8558 0.6649 0.8174 0.7824 Burstiness 7.0723 7.1217 1.0825 13.1220 0.0194 0.0230
  50. 50. Summary • We can move beyond the “who” of variation and into “how” and “why” • Indexical fields are a useful conceptual tool and we can use them to understand constraints on meaning • It seems likely that many indexical fields are structured by axes like self/other-orientation – Which are made visible to listeners and appraised by them • Rate is not the only thing that matters for emotion – Burstiness also communicates the drama of the situation – It is unlikely that people go to the extent that Shatner does – But there’s reason to believe that tempo may be as useful—or more so—than simple rates
  51. 51. Thank you! • Collins, S. 1989. Subjective and autonomic responses to Western classical music. Unpublished doctoral dissertation, University of Manchester, UK • Eckert, P. (2008). Variation and the indexical field. Journal of Sociolinguistics, 12(4), 453–476. • Huson, D., D. Richter, C. Rausch, T. Dezulian, M. Franz and R. Rupp. (2007). Dendroscope: An interactive viewer for large phylogenetic trees . BMC Bioinformatics 8:460, 2007, software freely available from www.dendroscope.org • de Jong, N. H., and T. Wempe. (2009). Praat script to detect syllable nuclei and measure speech rate automatically. Behavior research methods, 41(2), 385. • Juslin, P. N., and P. Laukka. (2003). Communication of emotions in vocal expression and music performance: Different channels, same code?. Psychological Bulletin, 129(5), 770–814. • Kendall, T. (2010). Language Variation and Sequential Temporal Patterns of Talk. Linguistics Department, Stanford University: Palo Alto, CA. February. • Kendall, T. (2009). Speech Rate, Pause, and Linguistic Variation: An Examination Through the Sociolinguistic Archive and Analysis Project, Doctoral Dissertation. Durham, NC: Duke University. • Scherer, K. (2003). Vocal communication of emotion: a review of research paradigms. Speech Communication, 40, 227-256. • Scherer, K. R. (1981). Speech and emotional states. Speech evaluation in psychiatry, 189–220. • Schnoebelen, T. (2009). The social meaning of tempo. http://www.stanford.edu/~tylers/notes/socioling/Social_meaning_tempo_Schnoebelen_3-23- 09.pdf • Scherer, K. 2003. Vocal communication of emotion: a review of research paradigms, Speech Comm. 40 227–256. • Scherer, K. and J. Oshinsky. (1977). Cue utilization in emotion attribution from auditory stimuli. Motiv. Emot. 1, 331–346. • Ververidis, D., and C. Kotropoulos. (2006). Emotional speech recognition: Resources, features, and methods. Speech Communication, 48(9), 1162– 1181. • Special thanks to Penny Eckert, John Rickford, Kate Geenberg, Kyuwon Moon, Roey Gafter, and Mathew Lodge • Also, fwiw, I’ve put together a lot of essays and reading notes about language and emotion here: – http://www.stanford.edu/~tylers/emotions.shtml
  52. 52. Appendix
  53. 53. Why look at TV/movies for style? • Actors are a good source for studies of style since they make vivid the cues that are more mixed and grey in real life. “The act that one does, the act that one performs, is, in a sense, an act that has been going on before one arrived on the scene” (Butler 1988: 526). Butler is talking about gender, but this idea applies to acting as well. Actors don’t really create anything out of whole cloth. They assemble bits and pieces. It would be difficult to analyze the acoustic signal of wooden acting, since we’d be measuring perceptions of lack, but even histrionic, scene-chewing samples offer us speech cues associated with various social categories. Again, the assumption is that actors use stylistic resources that their audiences can be expected to understand. If audiences uniformly agree on what a performance expresses, it doesn’t necessarily matter what the intention was. We’re after that shared social meaning and the components that comprise it, though we may be giving up the psychophysiological effects on the voice that happen under natural conditions. • Writers create scenes of dramatic interest, so that there is also a higher proportion of arousal in a scene than in daily life.
  54. 54. Overwhelmed Other-oriented Overwhelming Authoritative Persuading

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