Journal of Audiology & Otology

The Korean Audiology Society (대한청각학회)
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Effect of Music Training on Categorical Perception of Speech and Music

  • L., Yashaswini (Department of Audiology, All India Institute of Speech and Hearing) ;
  • Maruthy, Sandeep (Department of Audiology, All India Institute of Speech and Hearing)
  • Received : 2019.12.20
  • Accepted : 2020.04.17
  • Published : 2020.07.20
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Abstract

Background and Objectives: The aim of this study is to evaluate the effect of music training on the characteristics of auditory perception of speech and music. The perception of speech and music stimuli was assessed across their respective stimulus continuum and the resultant plots were compared between musicians and non-musicians. Subjects and Methods: Thirty musicians with formal music training and twenty-seven non-musicians participated in the study (age: 20 to 30 years). They were assessed for identification of consonant-vowel syllables (/da/ to /ga/), vowels (/u/ to /a/), vocal music note (/ri/ to /ga/), and instrumental music note (/ri/ to /ga/) across their respective stimulus continuum. The continua contained 15 tokens with equal step size between any adjacent tokens. The resultant identification scores were plotted against each token and were analyzed for presence of categorical boundary. If the categorical boundary was found, the plots were analyzed by six parameters of categorical perception; for the point of 50% crossover, lower edge of categorical boundary, upper edge of categorical boundary, phoneme boundary width, slope, and intercepts. Results: Overall, the results showed that both speech and music are perceived differently in musicians and non-musicians. In musicians, both speech and music are categorically perceived, while in non-musicians, only speech is perceived categorically. Conclusions: The findings of the present study indicate that music is perceived categorically by musicians, even if the stimulus is devoid of vocal tract features. The findings support that the categorical perception is strongly influenced by training and results are discussed in light of notions of motor theory of speech perception.

Keywords

Acknowledgement

We would like to thank the All India Institute of Speech and Hearing, Mysuru, for providing the necessary infrastructure and facilities to carry out the research. We would extend our sincere gratitude to all the participants of the study for their time and cooperation. No external source of funding was received to carry out the study.

References

  1. Gerrits E, Schouten ME. Categorical perception depends on the discrimination task. Percept Psychophys 2004;66:363-76. https://doi.org/10.3758/BF03194885
  2. Prather JF, Nowicki S, Anderson RC, Peters S, Mooney R. Neural correlates of categorical perception in learned vocal communication. Nat Neurosci 2009;12:221-8. https://doi.org/10.1038/nn.2246
  3. Eimas PD, Siqueland ER, Jusczyk P, Vigorito J. Speech perception in infants. Science 1971;171:303-6. https://doi.org/10.1126/science.171.3968.303
  4. Mody M, Studdert-Kennedy M, Brady S. Speech perception deficits in poor readers: auditory processing or phonological coding? J Exp Child Psychol 1997;64:199-231. https://doi.org/10.1006/jecp.1996.2343
  5. Liberman AM, Mattingly IG. The motor theory of speech perception revised. Cognition 1985;21:1-36. https://doi.org/10.1016/0010-0277(85)90021-6
  6. Jusczyk PW, Rosner BS, Cutting JE, Foard CF, Smith LB. Categorical perception of nonspeech sounds by 2-month-old infants. Percept Psychophys 1977;21:50-4. https://doi.org/10.3758/BF03199467
  7. Micheyl C, Delhommeau K, Perrot X, Oxenham AJ. Influence of musical and psychoacoustical training on pitch discrimination. Hear Res 2006;219:36-47. https://doi.org/10.1016/j.heares.2006.05.004
  8. Deguchi C, Boureux M, Sarlo M, Besson M, Grassi M, Schon D, et al. Sentence pitch change detection in the native and unfamiliar language in musicians and non-musicians: behavioral, electrophysiological and psychoacoustic study. Brain Res 2012;1455:75-89. https://doi.org/10.1016/j.brainres.2012.03.034
  9. Oxenham AJ, Fligor BJ, Mason CR, Kidd G Jr. Informational masking and musical training. J Acoust Soc Am 2003;114:1543-9. https://doi.org/10.1121/1.1598197
  10. Rammsayer T, Altenmuller E. Temporal information processing in musicians and nonmusicians. Music Percept 2006;24:37-48. https://doi.org/10.1525/mp.2006.24.1.37
  11. Bidelman GM, Moreno S, Alain C. Tracing the emergence of categorical speech perception in the human auditory system. Neuroimage 2013;79:201-12. https://doi.org/10.1016/j.neuroimage.2013.04.093
  12. Bidelman GM, Weiss MW, Moreno S, Alain C. Coordinated plasticity in brainstem and auditory cortex contributes to enhanced categorical speech perception in musicians. Eur J Neurosci 2014;40:2662-73. https://doi.org/10.1111/ejn.12627
  13. Burns EM, Ward WD. Categorical perception--phenomenon or epiphenomenon: evidence from experiments in the perception of melodic musical intervals. J Acoust Soc Am 1978;63:456-68. https://doi.org/10.1121/1.381737
  14. Bidelman GM, Alain C. Musical training orchestrates coordinated neuroplasticity in auditory brainstem and cortex to counteract age-related declines in categorical vowel perception. J Neurosci 2015;35:1240-9. https://doi.org/10.1523/JNEUROSCI.3292-14.2015
  15. Wu H, Ma X, Zhang L, Liu Y, Zhang Y, Shu H. Musical experience modulates categorical perception of lexical tones in native Chinese speakers. Front Psychol 2015;6:436. https://doi.org/10.3389/fpsyg.2015.00436
  16. Strange W. Evolving theories of vowel perception. J Acoust Soc Am 1989;85:2081-7. https://doi.org/10.1121/1.397860
  17. Cutting JE, Rosner BS. Categories and boundaries in speech and music. Percept Psychophys 1974;16:564-70. https://doi.org/10.3758/BF03198588
  18. Siegel JA, Siegel W. Absolute identification of notes and intervals by musicians. Percept Psychophys 1977;21:143-52. https://doi.org/10.3758/BF03198717
  19. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39:175-91. https://doi.org/10.3758/BF03193146
  20. Vaidyanath R, Yathiraj A. Screening checklist for auditory processing in adults (SCAP-A): development and preliminary findings. J Hear Sci 2014;4:33-43. https://doi.org/10.17430/891026
  21. American National Standard Institute. (R2008) AS 1-1999. Maximum permissible ambient noise levels for audiometric test rooms. New York, USA: American National Standards Institute, Inc.;1999.
  22. Venkatesan S. Ethical guidelines for bio-behavioral research. Mysuru, India: All India Institute of Speech and Hearing;2009.
  23. Doughty JM. The effect of psychophysical method and context on pitch and loudness functions. J Exp Psychol 1949;39:729-45. https://doi.org/10.1037/h0060307
  24. Powlin AC. Awareness and attitude towards stuttering among normal school going children [dissertation]. Karnataka: University of Mysore;2006.
  25. Powlin AC. Effect of temporal and spectral variations on phoneme identification skills in late talking children [dissertation]. Karnataka: University of Mysore;2009.
  26. Pastore RE, Schmuckler MA, Rosenblum L, Szczesiul R. Duplex perception with musical stimuli. Percept Psychophys 1983;33:469-74. https://doi.org/10.3758/BF03202898
  27. Cutting JA, Pisoni DB. An information-processing approach to speech perception. In: Implications of basic research in speech and language for the school and clinic (eds. Kavanagh JF, Strange W). Cambridge: MIT Press;1978.