Auditory-vocal integration impairment: New challenges and opportunities for voice assessment and therapy

Alteración de la integración auditivo-vocal: nuevos retos y oportunidades para la evaluación y la terapia de la voz

Published 2021-12-18

Open | Download
PDF Icon Flip Icon XML Icon
Issue
Vol. 3 No. 2 (2021)
Section
Reflection article
How to Cite
1.
Auditory-vocal integration impairment: New challenges and opportunities for voice assessment and therapy. Rev. Investig. Innov. Cienc. Salud [Internet]. 2021 Dec. 18 [cited 2024 Nov. 23];3(2):87-9. Available from: https://riics.info/index.php/RCMC/article/view/62
DOI

https://doi.org/10.46634/riics.62
Dimensions
PlumX
license
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Adrián Castillo-Allendes
Department of Communicative Sciences and Disorders; Michigan State University; East Lansing; United States.
    https://orcid.org/0000-0002-9511-6203
    Francisco Contreras-Ruston
    Perception, Attention and Representation Lab; Department of Cognition, Development and Educational Psychology; Universidad de Barcelona; Barcelona; España.
      https://orcid.org/0000-0001-5766-8616
      Jeff Searl
      Department of Communicative Sciences and Disorders; Michigan State University; East Lansing; United States.
        https://orcid.org/0000-0002-4442-1208
        Show authors biography

        Jeff Searl,

        Jeff Searl is a professor of the Department of Communicative Sciences & Disorders in Michigan State University. Searl’s faculty roles have focused almost exclusively on graduate student training at the Master’s degree level (training clinicians) and Ph.D. level (training research scientists). As a researcher, his primary areas of interest focus communication after treatment for head and neck cancer, laryngeal voice disorders, and articulatory changes associated with neurodegenerative diseases.

        This reflection paper addresses the importance of the interaction between voice perception and voice production, emphasizing the processes of auditory-vocal integration that are not yet widely reported in the context of voice clinicians. Given the above, this article seeks to 1) highlight the important link between voice production and voice perception and 2) consider whether this relationship might be exploited clinically for diagnostic purposes and therapeutic benefit. Existing theories on speech production and its interaction with auditory perception provide context for discussing why the evaluation of auditory-vocal processes could help identify associated origins of dysphonia and inform the clinician around appropriate management strategies. Incorporating auditory-vocal integration assessment through sensorimotor adaptation paradigm testing could prove to be an important addition to voice assessment protocols at the clinical level. Further, if future studies can specify the means to manipulate and enhance a person’s auditory-vocal integration, the efficiency of voice therapy could be increased, leading to improved quality of life for people with voice disorders.

        Article visits 724 | PDF visits 402

        1. Liberman AM, Mattingly IG. The motor theory of speech perception revised. Cognition [Internet]. 1985 Oct;21(1):1–36. doi: https://doi.org/10.1016/0010-0277(85)90021-6
        2. Fowler CA. Speech Perception as a Perceptuo-Motor Skill. In: Hickok G, Small S, editors. Neurobiology of Language [Internet]. Elsevier; 2016. p. 175–84. doi: https://doi.org/10.1016/B978-0-12-407794-2.00015-8
        3. Lotto AJ, Holt LL. Speech Perception. In: Hickok G, Small S, editors. Neurobiology of Language [Internet]. Elsevier; 2016 [cited 2021 Mar 9]. p. 185–94. doi: https://doi.org/10.1016/B978-0-12-407794-2.00016-X
        4. Kuang J, Liberman M. Integrating Voice Quality Cues in the Pitch Perception of Speech and Non-speech Utterances. Front Psychol [Internet]. 2018 Nov 29;9. doi: https://doi.org/10.3389/fpsyg.2018.02147
        5. Zhang Z. Mechanics of human voice production and control. J Acoust Soc Am [Internet]. 2016 Oct;140(4):2614–35. doi: https://doi.org/10.1121/1.4964509
        6. Liberman AM, Delattre P, Cooper FS. The Role of Selected Stimulus-Variables in the Perception of the Unvoiced Stop Consonants. Am J Psychol [Internet]. 1952 Oct;65(4):497. doi: https://doi.org/10.2307/1418032
        7. Liberman AM, Delattre PC, Gerstman LJ, Cooper FS. Tempo of frequency change as a cue for distinguishing classes of speech sounds. J Exp Psychol [Internet]. 1956;52(2):127–37. doi: http://doi.apa.org/getdoi.cfm?doi=10.1037/h0041240
        8. Liberman AM, Harris KS, Hoffman HS, Griffith BC. The discrimination of speech sounds within and across phoneme boundaries. J Exp Psychol [Internet]. 1957;54(5):358–68. doi: http://doi.apa.org/getdoi.cfm?doi=10.1037/h0044417
        9. Hillenbrand JM, Houde RA. Role of Fo and Amplitude in the Perception of Intervocalic Glottal Stops. J Speech, Lang Hear Res [Internet]. 1996 Dec;39(6):1182–90. doi: https://doi.org/10.1044/jshr.3906.1182
        10. Hillenbrand J, Getty LA, Clark MJ, Wheeler K. Acoustic characteristics of American English vowels. J Acoust Soc Am [Internet]. 1995 May;97(5):3099–111. doi: https://doi.org/10.1121/1.411872
        11. Morrison GS, Assmann PF. Vowel Inherent Spectral Change [Internet]. Morrison GS, Assmann PF, editors. Vowel Inherent Spectral Change. Berlin, Heidelberg: Springer Berlin Heidelberg; 2013. p. 1–286. Available from: http://link.springer.com/10.1007/978-3-642-14209-3
        12. Patel S, Nishimura C, Lodhavia A, Korzyukov O, Parkinson A, Robin DA, et al. Understanding the mechanisms underlying voluntary responses to pitch-shifted auditory feedback. J Acoust Soc Am [Internet]. 2014 May;135(5):3036–44. doi: https://doi.org/10.1121/1.4870490
        13. Parkinson AL, Flagmeier SG, Manes JL, Larson CR, Rogers B, Robin DA. Understanding the neural mechanisms involved in sensory control of voice production. Neuroimage [Internet]. 2012 May;61(1):314–22. doi: https://doi.org/10.1016/j.neuroimage.2012.02.068
        14. Patel RR, Awan SN, Barkmeier-Kraemer J, Courey M, Deliyski D, Eadie T, et al. Recommended protocols for instrumental assessment of voice: American speech-language-hearing association expert panel to develop a protocol for instrumental assessment of vocal function. Am J Speech-Language Pathol [Internet]. 2018 Aug 1 [cited 2021 Mar 9];27(3):887–905. doi: https://doi.org/10.1044/2018_AJSLP-17-0009
        15. Whittico TH, Ortiz AJ, Marks KL, Toles LE, Van Stan JH, Hillman RE, et al. Ambulatory monitoring of Lombard-related vocal characteristics in vocally healthy female speakers. J Acoust Soc Am [Internet]. 2020 Jun;147(6):EL552–8. doi: https://doi.org/10.1121/10.0001446
        16. Junqua J. The Lombard reflex and its role on human listeners and automatic speech recognizers. J Acoust Soc Am [Internet]. 1993 Jan;93(1):510–24. doi: https://doi.org/10.1121/1.405631
        17. Lu Y, Cooke M. Speech production modifications produced by competing talkers, babble, and stationary noise. J Acoust Soc Am [Internet]. 2008 Nov;124(5):3261–75. doi: https://doi.org/10.1121/1.2990705
        18. Alghamdi N, Maddock S, Marxer R, Barker J, Brown GJ. A corpus of audio-visual Lombard speech with frontal and profile views. J Acoust Soc Am [Internet]. 2018 Jun;143(6):EL523–9. doi: https://doi.org/10.1121/1.5042758
        19. Quedas A, de Campos Duprat A, Gasparini G. Lombard’s effect’s implication in intensity, fundamental frequency and stability on the voice of individuals with Parkinson’s disease. Braz J Otorhinolaryngol [Internet]. 2007 Sep;73(5):675–83. doi: https://doi.org/10.1016/S1808-8694(15)30129-4
        20. Purcell DW, Munhall KG. Compensation following real-time manipulation of formants in isolated vowels. J Acoust Soc Am [Internet]. 2006 Apr;119(4):2288–97. doi: https://doi.org/10.1121/1.2173514
        21. Larson CR, Burnett TA, Bauer JJ, Kiran S, Hain TC. Comparison of voice Fo responses to pitch-shift onset and offset conditions. J Acoust Soc Am [Internet]. 2001 Dec;110(6):2845–8. doi: https://doi.org/10.1121/1.1417527
        22. Tremblay P, Dick AS. Broca and Wernicke are dead, or moving past the classic model of language neurobiology. Brain Lang [Internet]. 2016 Nov;162:60–71. doi: https://doi.org/10.1016/j.bandl.2016.08.004
        23. Dick AS, Bernal B, Tremblay P. The Language Connectome. Neurosci [Internet]. 2014 Oct 15;20(5):453–67. doi: https://doi.org/10.1177/1073858413513502
        24. Guenther FH, Hickok G. Role of the auditory system in speech production. In: Aminoff M, Boller F, Swaab D, editora. Handbook of Clinical Neurology. Elsevier B.V.; 2015. p. 161–75. doi: https://doi.org/10.1016/B978-0-444-62630-1.00009-3
        25. Nasios G, Dardiotis E, Messinis L. From Broca and Wernicke to the Neuromodulation Era: Insights of Brain Language Networks for Neurorehabilitation. Behav Neurol [Internet]. 2019 Jul 22;2019:1–10. doi: https://doi.org/10.1155/2019/9894571
        26. Hickok G. Computational neuroanatomy of speech production. Nat Rev Neurosci [Internet]. 2012 Feb 5;13(2):135–45. doi: https://doi.org/10.1038/nrn3158
        27. Kearney E, Nieto-Castañón A, Weerathunge HR, Falsini R, Daliri A, Abur D, et al. A Simple 3-Parameter Model for Examining Adaptation in Speech and Voice Production. Front Psychol [Internet]. 2020 Jan 21;10. doi: https://doi.org/10.3389/fpsyg.2019.02995
        28. Perkell JS. Movement goals and feedback and feedforward control mechanisms in speech production. J Neurolinguistics [Internet]. 2012 Sep;25(5):382–407. doi: https://doi.org/10.1016/j.jneuroling.2010.02.011
        29. Tourville JA, Guenther FH. The DIVA model: A neural theory of speech acquisition and production. Lang Cogn Process [Internet]. 2011 Aug;26(7):952–81. doi: https://doi.org/10.1080/01690960903498424
        30. Abur D, Lester-Smith RA, Daliri A, Lupiani AA, Guenther FH, Stepp CE. Sensorimotor adaptation of voice fundamental frequency in Parkinson’s disease. PLoS One [Internet]. 2018 Jan 26;13(1):e0191839. doi: https://doi.org/10.1371/journal.pone.0191839
        31. Houde JF, Nagarajan SS. Speech Production as State Feedback Control. Front Hum Neurosci [Internet]. 2011;5. doi: https://doi.org/10.3389/fnhum.2011.00082
        32. Stepp CE, Lester-Smith RA, Abur D, Daliri A, Pieter Noordzij J, Lupiani AA. Evidence for auditory-motor impairment in individuals with hyperfunctional voice disorders [Internet]. Journal of Speech, Language, and Hearing Research. American Speech-Language-Hearing Association; 2017 [cited 2021 Mar 10];60(6):1545–50. doi: https://doi.org/10.1044/2017_JSLHR-S-16-0282
        33. Jones JA, Munhall KG. Perceptual calibration of F0 production: Evidence from feedback perturbation. J Acoust Soc Am [Internet]. 2000 [cited 2021 Mar 9];108(3):1246. doi: https://doi.org/10.1121/1.1288414
        34. Aronson AE. Clinical Voice Disorders (3rd Ed). Thieme; 1990.
        35. Galindo GE, Peterson SD, Erath BD, Castro C, Hillman RE, Zañartu M. Modeling the Pathophysiology of Phonotraumatic Vocal Hyperfunction With a Triangular Glottal Model of the Vocal Folds. J Speech, Lang Hear Res [Internet]. 2017 Sep 18;60(9):2452–71. doi: https://doi.org/10.1044/2017_JSLHR-S-16-0412
        36. Weerathunge HR, Abur D, Enos NM, Brown KM, Stepp CE. Auditory-Motor Perturbations of Voice Fundamental Frequency: Feedback Delay and Amplification. J Speech, Lang Hear Res [Internet]. 2020 Sep 15;63(9):2846–60. doi: https://doi.org/10.1044/2020_JSLHR-19-00407
        37. Arends N, Povel DJ, Van Os E, Speth L. Predicting voice quality of deaf speakers on the basis of glottal characteristics. J Speech Hear Res [Internet]. 1990 [cited 2021 Mar 9];33(1):116–22. doi: https://doi.org/10.1044/jshr.3301.116
        38. Clark A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav Brain Sci [Internet]. 2013 Jun 10 [cited 2021 Mar 9];36(3):181–204. doi: https://doi.org/10.1017/S0140525X12000477
        39. Lester-Smith RA, Daliri A, Enos N, Abur D, Lupiani AA, Letcher S, et al. The relation of articulatory and vocal auditory–motor control in typical speakers. J Speech, Lang Hear Res [Internet]. 2020 Nov 1 [cited 2021 Mar 9];63(11):3628–42. doi: https://doi.org/10.1044/2020_JSLHR-20-00192
        40. Lee SH, Yu JF, Fang TJ, Lee GS. Vocal fold nodules: A disorder of phonation organs or auditory feedback? Clin Otolaryngol [Internet]. 2019 Nov 1 [cited 2021 Mar 9];44(6):975–82. doi: https://doi.org/10.1111/coa.13417
        41. Escera C, López-Caballero F, Gorina-Careta N. The potential effect of forbrain as an altered auditory feedback device. J Speech, Lang Hear Res [Internet]. 2018 Apr 1 [cited 2021 Mar 9];61(4):801–10. doi: https://doi.org/10.1044/2017_JSLHR-S-17-0072
        42. Li Y, Tan M, Fan H, Wang EQ, Chen L, Li J, et al. Neurobehavioral Effects of LSVT® LOUD on Auditory-Vocal Integration in Parkinson’s Disease: A Preliminary Study. Front Neurosci [Internet]. 2021 Feb 26;15. doi: https://doi.org/10.3389/fnins.2021.624801
        43. Ramig LO, Countryman S, O’Brien C, Hoehn M, Thompson L. Intensive speech treatment for patients with Parkinson’s disease: Short- and long-term comparison of two techniques. Neurology [Internet]. 1996 Dec 1;47(6):1496–504. doi: https://doi.org/10.1212/WNL.47.6.1496
        44. Narayana S, Fox PT, Zhang W, Franklin C, Robin DA, Vogel D, et al. Neural correlates of efficacy of voice therapy in Parkinson’s disease identified by performance-correlation analysis. Hum Brain Mapp [Internet]. 2010;31:222-236. doi: https://doi.org/10.1002/hbm.20859
        45. Segawa JA, Tourville JA, Beal DS, Guenther FH. The Neural Correlates of Speech Motor Sequence Learning. J Cogn Neurosci [Internet]. 2015 Apr;27(4):819–31. doi: https://doi.org/10.1162/jocn_a_00737
        Publish with RIICS

        Scimago

        Most read in the last 30 days

        Sistema OJS 3.4.0.7 - Metabiblioteca |