The effect of healthy aging on within-speaker rhythmic variability: A case study on Noam Chomsky
DOI:
https://doi.org/10.3989/loquens.2019.060Keywords:
vocal aging, speech rhythm, rate measures, within-speaker rhythmic variabilityAbstract
Speech rhythm varies noticeably from language to language, and within the same language as a function of numerous linguistic, prosodic and speaker-dependent factors, among which is the speaker’s age. Cross-sectional studies comparing the acoustic characteristics of young and old voices have documented that healthy aging affects speech rhythm variability. This kind of studies, however, presents one fundamental limitation: They group together people with different life experiences, healthy conditions and aging rate. This makes it very difficult to disentangle the effect of aging from that of other factors when interpreting the rhythmic differences between younger and older adults. In the present paper, we overcame such difficulty by tracing rhythmic variability within one single individual longitudinally. We examined 5 public talks held by Noam Chomsky, from when he was 40 to when he was 89. Within-speaker rhythmic variability was quantified through a variety of rate measures (segment/consonant and vowel rate) and rhythmic metrics (%V, %Vn, nPVI-V, n-PVI-C). The results showed that physiological aging affected speech rate measures, but not the durational characteristics of vocalic and consonantal intervals. More longitudinal data from numerous speakers of the same language are necessary to identify generalizable patterns in age-related rhythmic variability.
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References
Amerman, J. D., & Parnell, M. M. (1992). Speech timing strategies in elderly adults. Journal of Phonetics, 20, 65-76.
Arvaniti, A. (2012). The usefulness of metrics in the quantification of speech rhythm. Journal of Phonetics, 40, 351-373. https://doi.org/10.1016/j.wocn.2012.02.003
Bilodeau-Mercure, M., & Tremblay, P. (2016). Age differences in sequential speech production: Articulatory and physiological factors. Journal of the American Geriatrics Society, 64, e177-e182. https://doi.org/10.1111/jgs.14491 PMid:27783395
Boersma, P., & Weenink, D. (2018). Praat: Doing phonetics by computer [Computer Program]. Version 6.0.39. www.praat.org
Dellwo, V. (2006). Rhythm and speech rate: A variation coefficient for deltaC. In P. Karnowski & I. Szigetieds (Eds.), Language and languag processing (pp. 231-241). Frankfurt am Main: Peter Lang.
Dellwo, V., & Fourcin, A. (2013). Rhythmic characteristics of voice between and within languages. TRANEL - Travaux neuchâtelois de linguistique, 59, 87-107.
Dellwo, V., Leemann, A., & Kolly, M.-J. (2015). Rhythmic variability between speakers: Articulatory, prosodic, and lexical factors. The Journal of the Acoustical Society of America, 137, 1513-1528. https://doi.org/10.1121/1.4906837 PMid:25786962
Fletcher, A. R., & McAuliffe, M. J. (2015). The relationship between speech segment duration and vowel centralization in a group of older speakers. The Journal of the Acoustical Society of America, 138, 2-32. https://doi.org/10.1121/1.4930563 PMid:26520296
Grabe, E., & Low, E. L. (2002). Durational variability in speech and the rhythm class hypothesis. In C. Gussenhoven & N. Warner (Eds.), Laboratory Phonology 7 (pp. 515-546). Berlin: De Gruyter Mouton.
He, L. (2018). Development of speech rhythm in first language: The role of syllable intensity variability. The Journal of the Acoustical Society of America, 143, EL463-EL467. https://doi.org/10.1121/1.5042083 PMid:29960429
He, L., & Dellwo. V. (2014). Speaker idiosyncratic variability of intensity across syllables. In Proceedings of the 15th Annual Conference of the International Speech Communication Association (INTERSPEECH-2014), pp. 233-237. Retrieved from https://www.isca-speech.org/archive/archive_papers/interspeech_2014/i14_0233.pdf
He, L., & Dellwo, V. (2016). The role of syllable intensity in between-speaker rhythmic variability. International Journal of Speech, Language and the Law, 23, 243-273. https://doi.org/10.1558/ijsll.v23i2.30345
He, L., & Dellwo, V. (2017). Between-speaker variability in temporal organizations of intensity contours. The Journal of the Acoustical Society of America, 141, EL488-EL494. https://doi.org/10.1121/1.4983398 PMid:28599553
Kelly, F., Drygajlo, A., & Harte, N. (2012). Speaker verification with long-term ageing data. In Proceedings of the 5th IAPR International Conference on Biometrics (ICB), pp. 478-483. https://doi.org/10.1109/ICB.2012.6199796
Kisler, T., Reichel, U. D., & Schiel, F. (2017). Multilingual processing of speech via web services. Computer Speech & Language, 45(C), 326-347. https://doi.org/10.1016/j.csl.2017.01.005
Leemann, A., Kolly, M.-J., & Dellwo. V. (2014). Speaker-individuality in suprasegmental temporal features: Implications for forensic voice comparison. Forensic Science International, 238, 59-67. https://doi.org/10.1016/j.forsciint.2014.02.019 PMid:24675042
Linville, S. E. (2004). The aging voice. The American Speech-Language-Hearing Association (ASHA) Leader, pp. 12-21.
Liss, J. M., LeGendre, S., & Lotto, A. J. (2010). Discriminating dysarthria type from envelope modulation spectra. Journal of Speech, Language, and Hearing Research, 53, 1246-1255. https://doi.org/10.1044/1092-4388(2010/09-0121)
Liss, J. M., White, L., Mattys, S. L., Lansford, K., Lotto, A. J., Spitzer, S. M., & Caviness, J. N. (2009). Quantifying speech rhythm abnormalities in the dysarthrias. Journal of Speech Language and Hearing Research, 52, 1334-1352. https://doi.org/10.1044/1092-4388(2009/08-0208)
Mann, C. J. (2003). Observational research methods. Research design II: Cohort, cross sectional, and case-control studies. Emerging Medicine Journal, 20, 54-60. https://doi.org/10.1136/emj.20.1.54 PMid:12533370 PMCid:PMC1726024
Mefferd, A. S., & Corder, E. E. (2014). Assessing articulatory speed performance as a potential factor of slowed speech in older adults. Journal of Speech, Language, and Hearing Research, 57, 347-360. https://doi.org/10.1044/2014_JSLHR-S-12-0261 PMid:24686555
Niebuhr, O., Voße, J., & Brem, A. (2016). What makes a charismatic speaker? A Computer-based acoustic-prosodic analysis of Steve Jobs tone of voice. Computers in Human Behavior, 64, 366-382. https://doi.org/10.1016/j.chb.2016.06.059
Payne, E., Post, B., Astruc, L., Prieto, P., & Vanrell, M. d. M. (2009). Rhythmic modification in child directed speech. Oxford University Working Papers in Linguistics, Philology & Phonetics, 12, 123-144.
Payne, E., Post, B., Astruc, L., Prieto, P., & Vanrell, M. d. M. (2011). Measuring child rhythm. Language and Speech, 55, 1-27. https://doi.org/10.1177/0023830911417687 PMid:22783632
Pellegrino, E., He, L., & Dellwo, V. (2018). The effect of ageing on speech rhythm: A study on Zurich German. In Proceedings of the 9th International Conference on Speech Prosody, pp. 133-137. https://doi.org/10.21437/SpeechProsody.2018-27
Pettorino, M., Pellegrino, E. (2014). Age and rhythmic variations: A study on Italian. In Proceedings of the 15th Annual Conference of the International Speech Communication Association (INTERSPEECH-2014), pp. 1234-1237. Retrieved from https://www.isca-speech.org/archive/archive_papers/interspeech_2014/i14_1234.pdf
Pettorino, M., Pellegrino, E., & Maffia, M. (2014). 'Young' and 'old' voices: The prosodic auto-transplantation technique for speaker's age recognition. In Proceedings of the 7th International Conference on Speech Prosody, pp. 135-139.
Polyanskaya, L., & Ordin. M. (2015). Acquisition of speech rhythm in first language. The Journal of the Acoustical Society of America, 138, EL199-EL204. https://doi.org/10.1121/1.4929616 PMid:26428813
Prieto, P., Vanrell, M. d. M., Astruc, L., Payne, E., & Post, B. (2012). Phonotactic and phrasal properties of speech rhythm. Evidence from Catalan, English, and Spanish. Speech Communication, 54, 681-702. https://doi.org/10.1016/j.specom.2011.12.001
Ramig, L. A., & Ringel, R. L. (1983). Effects of physiological aging on selected acoustic characteristics of voice. Journal of Speech and Hearing Research, 26, 22-30. https://doi.org/10.1044/jshr.2601.22
Ramus, F., Nespor, M., & Mehler, J. (1999). Correlates of linguistic rhythm in the speech signal. Cognition, 73, 265-292. https://doi.org/10.1016/S0010-0277(99)00058-X
Schaie, K. W., & Hofer, S. M. (2001). Longitudinal studies in aging research. In K. W. Schaie & S. M. Hofer (Eds.), Handbook of psychology of aging (5th ed., pp. 53-77). San Diego: Academic Press.
Schiel, F. (1999). Automatic phonetic transcription of non-prompted speech. 14th International Congress of Phonetic Sciences (ICPhS-14), 607-610. Retrieved from https://www.internationalphoneticassociation.org/icphs-proceedings/ICPhS1999/papers/p14_0607.pdf
Tilsen, S., & Arvaniti, A. (2013). Speech rhythm analysis with decomposition of the amplitude envelope: Characterizing rhythmic patterns within and across languages. The Journal of the Acoustical Society of America, 134, 628-639. https://doi.org/10.1121/1.4807565 PMid:23862837
United Nations (2017). The World Population Prospects: the 2017 Revision (Report ESA/P/WP/248). New York: United Nations. Retrieved from https://esa.un.org/unpd/wpp/publications/files/wpp2017_keyfindings.pdf
Vipperla, R., Renals, S., & Frankel, J. (2010). Ageing voices: The effect of changes in voice parameters on ASR performance. EURASIP Journal on Audio, Speech, and Music Processing, 525783. https://doi.org/10.1186/1687-4722-2010-525783
White, L., & Mattys, S. L. (2007). Calibrating rhythm: First language and second language studies. Journal of Phonetics, 35, 501-522. https://doi.org/10.1016/j.wocn.2007.02.003
Wiget, L., White, L., Schuppler, B., Grenon, I., Rauch, O., & Mattys, S. L. (2010). How stable are acoustic metrics of contrastive speech rhythm? The Journal of the Acoustical Society of America, 127, 1559-1569. https://doi.org/10.1121/1.3293004 PMid:20329856
Yoon, T.-J. (2010). Capturing inter-speaker invariance using statistical measures of speech rhythm. In Proceedings of the 5th International Conference on Speech Prosody, pp. 1-4.
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