Virtual Reality Technology and Speech Analysis for People Who Stutter

  • Abeer Al-Nafjan Imam Mohammad Ibn Saud Islamic University, Saudi Arabia
  • Najwa Alghamdi Department of Information Technology, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia
  • Abdulaziz Almudhi Department of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
Keywords: virtual reality, stutter, speech analysis, rehabilitation


Virtual reality (VR) technology provides an interactive computer-generated experience that artificially simulates real-life situations by creating a virtual environment that looks real and stimulates the user’s feelings. During the past few years, the use of VR technology in clinical interventions for assessment, rehabilitation and treatment have received increased attention. Accordingly, many clinical studies and applications have been proposed in the field of mental health, including anxiety disorders. Stuttering is a speech disorder in which affected individuals have a problem with the flow of speech. This can manifest in the repetition and prolongation of words or phrases, as well as in involuntary silent pauses or blocks during which the individual is unable to produce sounds. Stuttering is often accompanied by a social anxiety disorder as a secondary symptom, which requires separate treatment. In this study, we evaluated the effectiveness of using a VR environment as a medium for presenting speech training tasks. In addition, we evaluated the accuracy of a speech analyzer module in detecting stuttering events.


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Schultheis, M.T., Himelstein, J.M., Rizzo, A.A., Virtual reality and neuropsychology: upgrading the current tools, The Journal of head trauma rehabilitation, Vol.17, pp.378–394, 2002. DOI:

Steuer, J., Defining Virtual Reality: Dimensions Determining Telepresence, Journal of Communication, Vol.42, pp.73–93, 1992. DOI:

Jackie, F., LeHong, H., Hype cycle for emerging technologies, 2011.

Panetta, K.: Top trends in the gartner hype cycle for emerging technologies, 2017.

Caughter, S., Dunsmuir, S., An exploration of the mechanisms of change following an integrated group intervention for stuttering, as perceived by school-aged children who stutter (CWS), Journal of Fluency Disorders, Vol.51, pp.8–23, 2017. DOI:

Brundage, S.B., Virtual reality augmentation for functional assessment and treatment of stuttering, Topics in Language Disorders. Vol.27, pp.254–271, 2007. DOI:

Brundage, S.B., Hancock, A.B., Real Enough: Using Virtual Public Speaking Environments to Evoke Feelings and Behaviors Targeted in Stuttering Assessment and Treatment, American Journal of Speech-Language Pathology. Vol.24, pp.139–149, 2015. DOI:

Guitar, B., Stuttering: An integrated approach to its nature and treatment. Lippincott Williams & Wilkins, 2013.

Louis, K.O., Measurement issues in fluency disorders, Current issues in stuttering research and practice, pp.69–94, 2014. DOI:

Bloodstein, O., & Ratner, N., A handbook on stuttering, S, San Diego, 1995.

Mulcahy, K., Hennessey, N., Beilby, J., Byrnes, M., Social anxiety and the severity and typography of stuttering in adolescents. Journal of Fluency Disorders, Vol.33, pp.306–319, 2008. DOI:

Brundage, S.B., Graap, K., Gibbons, K.F., Ferrer, M., Brooks, J., Frequency of stuttering during challenging and supportive virtual reality job interviews, Journal of Fluency Disorders, Vol.31, pp.325–339, 2006. DOI:

Brundage, S.B., Brinton, J.M., Hancock, A.B., Utility of virtual reality environments to examine physiological reactivity and subjective distress in adults who stutter, Journal of Fluency Disorders, Vol.50, pp.85–95, 2016. DOI:

Walkom, G., Virtual reality exposure therapy: To benefit those who stutter and treat social anxiety, International Conference on Interactive Technologies and Games: EduRob in Conjunction with iTAG, pp. 36–41, IEEE, 2016. DOI:

Scheurich, J.A., Beidel, D.C., Vanryckeghem, M., Exposure therapy for social anxiety disorder in people who stutter: An exploratory multiple baseline design. Journal of Fluency Disorders, Vol.59, pp.21–32, 2019. DOI:

Kourkounakis, T., Hajavi, A., Etemad, A., Detecting Multiple Speech Disfluencies Using a Deep Residual Network with Bidirectional Long Short-Term Memory, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp. 6089–6093, 2020. DOI:

Lowder, M.W., Maxfield, N.D., Ferreira, F., Processing of self-repairs in stuttered and non-stuttered speech. Language, Cognition and Neuroscience, Vol.35, pp.93–105, 2019. DOI:

Kostek, B., Czyzewski, A., Kaczmarek, A., Intelligent Processing of Stuttered Speech, Journal of Intelligent Information Systems, Vol.21, pp.143–171, 2003. DOI:

Al-Nafjan, A., Al-Wabil, A., AlMudhi, A., Hosny, M., Measuring and monitoring emotional changes in children who stutter. Computers in Biology and Medicine. Vol.102, pp.138–150, 2018. DOI:

Packman, A., Meredith, G., Technology and the evolution of clinical methods for stuttering, Journal of Fluency Disorders, Vol.36, pp.75–85, 2011. DOI:

Herchonvicz, A.L., Franco, C.R., Jasinski, M.G., A comparison of cloud-based speech recognition engines. Anais do Computer on the Beach, pp. 366–375, 2019.

How to Cite
Al-Nafjan, A., Alghamdi , N., & Almudhi , A. (2021). Virtual Reality Technology and Speech Analysis for People Who Stutter. EMITTER International Journal of Engineering Technology, 9(2), 326-338.