Influence of Smartphones and Software on Acoustic Voice Measures.

Elizabeth U. Grillo, Jenna N. Brosious, Staci L. Sorrell, Supraja Anand

Abstract


This study assessed the within-subject variability of voice measures captured using different recording devices (i.e., smartphones and head mounted microphone) and software programs (i.e., Analysis of Dysphonia in Speech and Voice (ADSV), Multi-dimensional Voice Program (MDVP), and Praat).  Correlations between the software programs that calculated the voice measures were also analyzed.  Results demonstrated no significant within-subject variability across devices and software and that some of the measures were highly correlated across software programs.  The study suggests that certain smartphones may be appropriate to record daily voice measures representing the effects of vocal loading within individuals.  In addition, even though different algorithms are used to compute voice measures across software programs, some of the programs and measures share a similar relationship. 


References


Boersma, P., & Weenink, D. (2015). Praat: Doing phonetics by computer [Computer program]. Version 6004. Retrieved from http://www.praat.org

Bhattacharyya, N. (2014). The prevalence of voice problems among adults in the United States. Laryngoscope, 124, 2359-2362.

Cohen, S. M. (2010). Self‐reported impact of dysphonia in a primary care population: An epidemiological study. Laryngoscope, 120, 2022-2032.

eMarketer (2014). Smartphone users worldwide will total 1.75 billion in 2014. Retrieved from http://www.emarketer.com/Article/Smartphone-Users-Worldwide-Will-Total-175-Billion-2014/1010536 http://telerehab.pitt.edu/ojs/index.php/Telerehab/editor/submissionEditing/6202

Fava, G., Oliveira, G., Baglione, M., Pimpinella, M., & Spitzer, J.B. (2016). The use of sound level meter apps in the clinical setting. American Journal of Speech-Language Pathology, 25, 14-28.

Grillo, E.U. & Fugowski, J.M. (2011). Voice characteristics of female physical education student teachers. Journal of Voice, 25, 149-157.

Hunter, E. J. (2012). Teacher response to ambulatory monitoring of voice. Logopedics Phoniatrics Vocology, 37, 133-135.

Kardous, C.A., & Shaw, P.B. (2014). Evaluation of smartphone sound measurement applications. JASA Express Letters, 135, 186-192.

Maryn, Y., De Bodt, M., & Roy, N. (2010). The acoustic voice quality index: Toward improved treatment outcomes assessment in voice disorders. Journal of Communication Disorders, 43, 161-174.

Mehta, D. D., Zanartu, M., Van Stan, J. H., Feng, S. W., Cheyne, H. A., & Hillman, R. E. (2013). Smartphone-based detection of voice disorders by long-term monitoring of neck acceleration features. In Body Sensor Networks (BSN), 2013 IEEE International Conference on IEEE, 1-6.

Mehta, D. D., Van Stan, J. H., Zañartu, M., Ghassemi, M., Guttag, J. V., Espinoza, V. M., Corets, J.P., Cheyne, H.A., & Hillman, R. (2015). Using ambulatory voice monitoring to investigate common voice disorders: Research update. Frontiers in Bioengineering and Biotechnology, 3, 155. doi:10.3389/fbioe.2015.00155

National Institute on Deafness and Other Communication Disorders (NIDCD). (2014). Statistics on voice speech and language. Retrieved from http://www.nidcd.nih.gov/health/voice/pages/whatis_vsl.aspx

Nielsen (2014). Mobile millennials: Over 85% of generation Y owns smartphones. Retrieved from http://www.nielsen.com/us/en/insights/news/2014/mobile-millennials-over-85-percent-of-generation-y-owns-smartphones.html

Nielsen (2015). So many apps, so much more time for entertainment. Retrieved from http://www.nielsen.com/us/en/insights/news/2015/so-many-apps-so-much-more-time-for-entertainment.html

Plichta, B. & Kornbluh, M. 2002. Digitizing speech recordings for archival purposes. Retrieved from http://www.historicalvoices.org/papers/audio_digitization.pdf

Uloza V., Padervinskis E., Vegiene A., Pribuisiene R., Saferis V., Vaiciukynas E., Gelzinis A., Verikas A. (2015). Exploring the feasibility of smart phone microphone for measurement of acoustic voice parameters and voice pathology screening. European Archives of Oto-Rhino-Laryngology , 272, 3391-3399.




DOI: https://doi.org/10.5195/ijt.2016.6202

  

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