DOI QR코드

DOI QR Code

A comparison of normalized formant trajectories of English vowels produced by American men and women

  • Yang, Byunggon (Department of English Education, Pusan National University)
  • Received : 2019.02.06
  • Accepted : 2019.03.05
  • Published : 2019.03.31

Abstract

Formant trajectories reflect the continuous variation of speakers' articulatory movements over time. This study examined formant trajectories of English vowels produced by ninety-three American men and women; the values were normalized using the scale function in R and compared using generalized additive mixed models (GAMMs). Praat was used to read the sound data of Hillenbrand et al. (1995). A formant analysis script was prepared, and six formant values at the corresponding time points within each vowel segment were collected. The results indicate that women yielded proportionately higher formant values than men. The standard deviations of each group showed similar patterns at the first formant (F1) and the second formant (F2) axes and at the measurement points. R was used to scale the first two formant data sets of men and women separately. GAMMs of all the scaled formant data produced various patterns of deviation along the measurement points. Generally, more group difference exists in F1 than in F2. Also, women's trajectories appear more dynamic along the vertical and horizontal axes than those of men. The trajectories are related acoustically to F1 and F2 and anatomically to jaw opening and tongue position. We conclude that scaling and nonlinear testing are useful tools for pinpointing differences between speaker group's formant trajectories. This research could be useful as a foundation for future studies comparing curvilinear data sets.

Keywords

References

  1. Bigi, B., & Hirst, D. (2018). Speech phonetization alignment and syllabification (SPPAS): A tool for the automatic analysis of speech prosody [Computer program]. Retrieved from http://www.sppas.org/
  2. Boersma, P., & Weenink, D. (2019). Praat: Doing phonetics by computer [Computer program]. Retrieved from http://www.fon.hum.uva.nl/praat/
  3. Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1-26. https://doi.org/10.1214/aos/1176344552
  4. Fant, G. (1973). Speech sounds and features. Cambridge, MA: MIT Press.
  5. Flynn, N. (2011). Comparing vowel formant normalisation procedures. York Papers in Linguistics Series, 2(11), 1-28.
  6. Fowler, C. A., & Housum, J. (1987). Talkers' signaling of "new" and "old" words in speech and listeners' perception and use of the distinction. Journal of Memory and Language, 26(5), 489-504. https://doi.org/10.1016/0749-596X(87)90136-7
  7. Hillenbrand, J., Getty, L. A., Clark, M. J., & Wheeler, K. (1995). Acoustic characteristics of American English vowels. Journal of the Acoustical Society of America, 97(5), 3099-3111. https://doi.org/10.1121/1.411872
  8. Lobanov, B. M. (1971). Classification of Russian vowels spoken by different speakers. Journal of the Acoustical Society of America, 49(2B), 606-608. https://doi.org/10.1121/1.1912396
  9. Nordstroem, P. E., & Lindblom, B. (1975, August). A normalization procedure for vowel formant data. International Congress of Phonetic Sciences (Paper #212). Leeds, UK.
  10. Peterson, G. E., & Barney, H. L. (1952). Control methods used in a study of vowels. Journal of the Acoustical Society of America, 24(2), 175-184. https://doi.org/10.1121/1.1906875
  11. Pickett, J. M. (1980). The sounds of speech communication: A primer of acoustic phonetics and speech perception (Perspectives in Audiology Series). Baltimore, MD.: University Park Press.
  12. R Core Team. (2019). R: A language and environment for statistical computing (version 3.5.1) [Computer software]. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from https://www.R-project.org/
  13. Renwick, M. E. L., & Ladd, D. R. (2016). Phonetic distinctiveness vs. lexical contrastiveness in Non-Robust phonemic contrasts. Laboratory Phonology, 7(1), 1-29. https://doi.org/10.5334/labphon.7
  14. Soskuthy, M. (2017). Generalised additive mixed models for dynamic analysis in linguistics: A practical introduction [Computing Research Repository]. Retrieved from https://arxiv.org/abs/1703.05339v1
  15. van Rij, J. (2015). Overview of GAMM analysis of time series data. Retrieved from http://www.sfs.uni-tuebingen.de/-jvanrij/Tutorial/GAMM.html
  16. Watt, D., & Fabricius, A. (2002). Evaluation of a technique for improving the mapping of multiple speakers' vowel spaces in the F1-F2 plane. Leeds Working Papers in Linguistics and Phonetics, 9, 159-173.
  17. Wood, S. N. (2006). Generalised additive mixed models: An introduction with R. Boca Raton, FL: CRC Press.
  18. Wright, R. (2003). Factors of lexical competition in vowel articulation. In J. Local, R. Ogden, & R. Temple (Eds.), Papers in laboratory phonology VI (pp. 75-87). Cambridge, UK: Cambridge University Press.
  19. Yang, B. (1990). Development of vowel normalization procedures: English and Korean (Ph.D. Dissertation). The University of Texas at Austin. Retrieved from http://fonetiks.info/bgyang/db/yangphd.pdf
  20. Yang, B. (1996). A comparative study of American English and Korean vowels produced by male and female speakers. Journal of Phonetics, 24(2), 245-261. https://doi.org/10.1006/jpho.1996.0013
  21. Yang, B. (2009). Formant trajectories of English vowels produced by American males. Phonetics and Speech Sciences, 1(3), 65-72.
  22. Yang, B. (2010). Formant trajectories of English high tense and lax vowel produced by Korean and American speakers. Korean Journal of Linguistics, 35(2), 407-421. https://doi.org/10.18855/lisoko.2010.35.2.005
  23. Yang, B. (2018). Pitch trajectories of English vowels produced by American men, women, and children. Phonetics and Speech Sciences, 10(4), 31-37. https://doi.org/10.13064/KSSS.2018.10.4.031