The role of temporal amplitude modulations in the political arena: Hillary Clinton vs. Donald Trump

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn 2017-August, Issue , 2017, Pages 2228-2232

  Bosker, Hans Rutger ^a,b  

^a MAX PLANCK INSTITUTE FOR PSYCHOLINGUISTICS   (Netherlands)

^b RADBOUD UNIVERSITY   (Netherlands)

Author keywords

Amplitude envelope; Amplitude modulations; Donald Trump; Hillary Clinton; Modulation spectrum; Speech rhythm

Indexed keywords

AMPLITUDE MODULATION; SPEECH; SPEECH COMMUNICATION; SPEECH RECOGNITION; SPEECH SYNTHESIS;

AMPLITUDE ENVELOPE; DONALD TRUMP; HILLARY CLINTON; MODULATION SPECTRUM; SPEECH RHYTHM;

MODULATION;

EID: 85039172109     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: 10.21437/Interspeech.2017-142     Document Type: Conference Paper

References (40)

1. F. Pellegrino, C. Coupé, and E. Marsico, "Across-language perspective on speech information rate," Language, vol. 87, pp. 539-558, 2011.
2. O. Ghitza, "Behavioral evidence for the role of cortical θ oscillations in determining auditory channel capacity for speech," Frontiers in psychology, vol. 5, p. 652, 2014.
3. E. Jacewicz, R. A. Fox, and L. Wei, "Between-speaker and within-speaker variation in speech tempo of American English," The Journal of the Acoustical Society of America, vol. 128, pp. 839-850, 2010.
4. H. Quené, "Multilevel modeling of between-speaker and within-speaker variation in spontaneous speech tempo," The Journal of the Acoustical Society of America, vol. 123, pp. 1104-1113, 2008.
5. J. Verhoeven, G. De Pauw, and H. Kloots, "Speech rate in a pluricentric language: A comparison between Dutch in Belgium and the Netherlands," Language and Speech, vol. 47, pp. 297-308, 2004.
6. O. Ghitza and S. Greenberg, "On the possible role of brain rhythms in speech perception: intelligibility of time-compressed speech with periodic and aperiodic insertions of silence," Phonetica, vol. 66, pp. 113-126, 2009.
7. S. Greenberg and T. Arai, "What are the essential cues for understanding spoken language?," IEICE Transactions on Information and Systems, vol. E87-D, pp. 1059-1070, 2004.
8. S. Greenberg, "Speaking in shorthand - A syllable-centric perspective for understanding pronunciation variation," Speech Communication, vol. 29, pp. 159-176, 1999.
9. N. Ding, A. Patel, L. Chen, H. Butler, C. Luo, and D. Poeppel, "Temporal modulations in speech and music," Neuroscience and Biobehavioral Reviews, Online version, 2017.
10. O. Ghitza, "Linking speech perception and neurophysiology: speech decoding guided by cascaded oscillators locked to the input rhythm," Frontiers in Psychology, vol. 2, 2011.
11. A.-L. Giraud and D. Poeppel, "Cortical oscillations and speech processing: emerging computational principles and operations," Nature Neuroscience, vol. 15, pp. 511-517, 2012.
12. J. E. Peelle and M. H. Davis, "Neural oscillations carry speech rhythm through to comprehension," Frontiers in psychology, vol. 3, 2012.
13. A. R. Bradlow, G M. Torretta, and D. B. Pisoni, "Intelligibility of normal speech I: Global and fine-grained acoustic-phonetic talker characteristics," Speech communication, vol. 20, pp. 255-272, 1996.
14. O. Ghitza, "On the role of theta-driven syllabic parsing in decoding speech: intelligibility of speech with a manipulated modulation spectrum," Frontiers in psychology, vol. 3, p. 238, 2012.
15. K. B. Doelling, L. H. Arnal, O. Ghitza, and D. Poeppel, "Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing," Neuroimage, vol. 85, pp. 761-768, 2014.
16. K. Aikawa and K. Ishizuka, "Noise-robust speech recognition using a new spectral estimation method "PHASOR"," in Proceedings of Acoustics, Speech, and Signal Processing (ICASSP). vol. 1, ed: IEEE, 2002, pp. I-397-I-400.
17. A. Cutler, "Segmentation problems, rhythmic solutions," Lingua, vol. 92, pp. 81-104, 1994.
18. A. Cutler and D. Norris, "The role of strong syllables in segmentation for lexical access," Journal of Experimental Psychology: Human perception and performance, vol. 14, p. 113, 1988.
19. A. Cutler and S. Butterfield, "Rhythmic cues to speech segmentation: Evidence from juncture misperception," Journal of Memory and Language, vol. 31, pp. 218-236, 1992.
20. H. R. Bosker, "Accounting for rate-dependent category boundary shifts in speech perception," Attention, Perception & Psychophysics, vol. 79, pp. 333-343, 2017.
21. H. Quené and R. Port, "Effects of timing regularity and metrical expectancy on spoken-word perception," Phonetica, vol. 62, pp. 1-13, 2005.
22. M. P. Roncaglia-Denissen, M. Schmidt-Kassow, and S. A. Kotz, "Speech rhythm facilitates syntactic ambiguity resolution: ERP evidence," PloS One, vol. 8, p. e56000, 2013.
23. K. Rothermich, M. Schmidt-Kassow, and S. A. Kotz, "Rhythm's gonna get you: regular meter facilitates semantic sentence processing," Neuropsychologia, vol. 50, pp. 232-244, 2012.
24. P. J. Essens and D.-J. Povel, "Metrical and nonmetrical representations of temporal patterns," Perception & Psychophysics, vol. 37, pp. 1-7, 1985.
25. C. Obermeier, S. A. Kotz, S. Jessen, T. Raettig, M. von Koppenfels, and W. Menninghaus, "Aesthetic appreciation of poetry correlates with ease of processing in event-related potentials," Cognitive, Affective, & Behavioral Neuroscience, vol. 16, pp. 362-373, 2016.
26. C. Obermeier, W. Menninghaus, M. von Koppenfels, T. Raettig, M. Schmidt-Kassow, S. Otterbein, et al, "Aesthetic and emotional effects of meter and rhyme in poetry," Frontiers in Psychology, vol. 4, 2013.
27. A. Rosenberg and J. Hirschberg, "Charisma perception from text and speech," Speech Communication, vol. 51, pp. 640-655, 2009.
28. O. Niebuhr, J. Voße, and A. Brem, "What makes a charismatic speaker? A computer-based acoustic-prosodic analysis of Steve Jobs tone of voice," Computers in Human Behavior, vol. 64, pp. 366-382, 2016.
29. F. D'Errico, R. Signorello, D. Demolin, and I. Poggi, "The perception of charisma from voice: A cross-cultural study," in Proceedings of Affective Computing and Intelligent Interaction (ACII), ed: IEEE, 2013, pp. 552-557.
30. F. Ramus, M. Nespor, and J. Mehler, "Correlates of linguistic rhythm in the speech signal," Cognition, vol. 73, pp. 265-292, 1999.
31. E. Grabe and E. L. Low, "Durational variability in speech and the rhythm class hypothesis," Laboratory Phonology, vol. 7, 2002.
32. L. White and S. L. Mattys, "Calibrating rhythm: First language and second language studies," Journal of Phonetics, vol. 35, pp. 501-522, 2007.
33. V. Dellwo, "Rhythm and speech rate: A variation coefficient for UΔC," in Language and Language-Processing, P. Karnowski and I. Szigeti, Eds., Frankfurt am Main: Peter Lang, 2006, pp. 231-241.
34. A. Loukina, G. Kochanski, B. Rosner, E. Keane, and C. Shih, "Rhythm measures and dimensions of durational variation in speech," The Journal of the Acoustical Society of America, vol. 129, pp. 3258-3270, 2011.
35. (2016, Sept 28, 2016). The First Presidential Debate: Hillary Clinton And Donald Trump (Full Debate) | NBC News. Available: https://www.youtube.com/watch?v=855Am6ovK7s
36. (2016, Oct 9, 2016). FULL VIDEO: Donald Trump vs Hillary Clinton - 2nd Presidential Debate. Available: https://www.youtube.com/watch?v=h-gkBUbU-F4
37. (2016, Oct 19, 2016). FULL VIDEO: Donald Trump vs Hillary Clinton - 3rd Presidential Debate. Available: https://www.youtube.com/watch?v=LsA6Gj8y8rU
38. J. C. Krause and L. D. Braida, "Acoustic properties of naturally produced clear speech at normal speaking rates," The Journal of the Acoustical Society of America, vol. 115, pp. 362-378, 2004.
39. H. R. Bosker and M. Cooke, "Rhythm in plain and Lombard speech," presented at the 9th Speech in Noise Workshop, Oldenburg, Germany, 2017.
40. Y. Tian, "Disfluencies in Trump and Clinton first presidential debate," in Proceedings of the conference Fluency and Disfluency Across Languages and Language Varieties, Louvain-la-Neuve, 2017, pp. 106-109.