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European Archives of Oto-Rhino-Laryngology

, Volume 275, Issue 4, pp 949–958 | Cite as

A comparison of Dysphonia Severity Index and Acoustic Voice Quality Index measures in differentiating normal and dysphonic voices

  • Virgilijus Uloza
  • Ben Barsties v. Latoszek
  • Nora Ulozaite-StanieneEmail author
  • Tadas Petrauskas
  • Youri Maryn
Laryngology

Abstract

Purpose

The aim of the study was to investigate and compare the feasibility and robustness of the Acoustic Voice Quality Index (AVQI) and the Dysphonia Severity Index (DSI) in diagnostic accuracy, differentiating normal and dysphonic voices.

Methods

A group of 264 subjects with normal voices (n = 105) and with various voice disorders (n = 159) were asked to read aloud a text and to sustain the vowel /a/. Both speech tasks were concatenated, and perceptually rated for dysphonia severity by five voice clinicians. They rated the Grade (G) and the overall dysphonia severity with a visual analog scale (VAS). All concatenated voice samples were acoustically analyzed to receive an AVQI score. For DSI analysis, the required voice parameters were obtained from the sustained phonation of the vowel /a/.

Results

The results achieved significant and marked concurrent validity between both auditory-perceptual judgment procedures and both acoustic voice measures. The DSI threshold (i.e., DSI = 3.30) pertaining to Gmean obtained reasonable sensitivity of 85.8% and specificity of 83.4%. For VASmean, the DSI threshold of 3.30 was determined also with reasonable sensitivity of 70.3% and excellent specificity of 93.9%. Also, the AVQI threshold (i.e., AVQI = 3.31) pertaining to Gmean demonstrated reasonable sensitivity of 78.1% and excellent specificity of 92.0%. For VASmean, an AVQI threshold of 3.33 was determined with excellent sensitivity of 97.0% and reasonable specificity of 81.8%.

Conlusion

The outcomes of the present study indicate comparable results between DSI and AVQI with a high level of validity to discriminate between normal and dysphonic voices. However, a higher level of accuracy was yielded for AVQI as a correlate of auditory perceptual judgment suggesting a reliable voice screening potential of AVQI.

Keywords

Dysphonia Acoustic Voice Quality Index Dysphonia Severity Index Acoustic voice analysis Voice assessment 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

Lithuanian State Data Protection Inspectorate for Working with Personal Patient Data [No. 2R-648 (2.6-1)].

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Maryn Y, Roy N, De Bodt M et al (2009) Acoustic measurement of overall voice quality: a meta-analysis. J Acoust Soc Am 126:2619–2634.  https://doi.org/10.1121/1.3224706 CrossRefPubMedGoogle Scholar
  2. 2.
    Roy N, Barkmeier-Kraemer J, Eadie T et al (2013) Evidence-based clinical voice assessment: a systematic review. Am J Speech Lang Pathol 22:212–226.  https://doi.org/10.1044/1058-0360(2012/12-0014)CrossRefPubMedGoogle Scholar
  3. 3.
    Linder R, Albers AE, Hess M et al (2008) Artificial neural network-based classification to screen for dysphonia using psychoacoustic scaling of acoustic voice features. J Voice 22:155–163.  https://doi.org/10.1016/j.jvoice.2006.09.003 CrossRefPubMedGoogle Scholar
  4. 4.
    Uloza V, Verikas A, Bacauskiene M et al (2011) Categorizing normal and pathological voices: automated and perceptual categorization. J Voice 25:700–708.  https://doi.org/10.1016/j.jvoice.2010.04.009 CrossRefPubMedGoogle Scholar
  5. 5.
    Wuyts FL, De Bodt MS, Molenberghs G et al (2000) The dysphonia severity index: an objective measure of vocal quality based on a multiparameter approach. J Speech Lang Hear Res 43:796–809.  https://doi.org/10.1044/jslhr.4303.796 CrossRefPubMedGoogle Scholar
  6. 6.
    Hussein Gaber AG, Liang FY, Yang JS et al (2014) Correlation among the dysphonia severity index (DSI), the RBH voice perceptual evaluation, and minimum glottal area in female patients with vocal fold nodules. J Voice 28:20–23.  https://doi.org/10.1016/j.jvoice.2013.08.002 CrossRefPubMedGoogle Scholar
  7. 7.
    Nemr K, Simões-Zenari M, de Souza GS et al (2015) Correlation of the Dysphonia Severity Index (DSI), Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), and gender in Brazilians with and without voice disorders. J Voice 30:765e7–765e11.  https://doi.org/10.1016/j.jvoice.2015.10.013 Google Scholar
  8. 8.
    Hakkesteegt MM, Brocaar MP, Wieringa MH (2010) The applicability of the dysphonia severity index and the voice handicap index in evaluating effects of voice therapy and phonosurgery. J Voice 24:199–205.  https://doi.org/10.1016/j.jvoice.2008.06.007 CrossRefPubMedGoogle Scholar
  9. 9.
    Salmen T, Ermakova T, Möller A et al (2017) The value of vocal extent measure (VEM) assessing phonomicrosurgical outcomes in vocal fold polyps. J Voice 31:114.e7–114.e15.  https://doi.org/10.1016/j.jvoice.2016.03.016 CrossRefGoogle Scholar
  10. 10.
    Maryn Y, De Bodt M, Roy N (2010) The Acoustic Voice Quality Index: toward improved treatment outcomes assessment in voice disorders. J Commun Disord 43:161–174.  https://doi.org/10.1016/j.jcomdis.2009.12.004 doiCrossRefPubMedGoogle Scholar
  11. 11.
    Maryn Y, Corthals P, Van Cauwenberge P et al (2010) Toward improved ecological validity in the acoustic measurement of overall voice quality: combining continuous speech and sustained vowels. J Voice 24:540–555.  https://doi.org/10.1016/j.jvoice.2008.12.014 CrossRefPubMedGoogle Scholar
  12. 12.
    Awan SN, Roy N, Dromey C (2009) Estimating dysphonia severity in continuous speech: application of a multi-parameter spectral/cepstral model. Clin Linguist Phon 23:825–841.  https://doi.org/10.3109/02699200903242988 CrossRefPubMedGoogle Scholar
  13. 13.
    Awan SN, Roy N, Zhang D, Cohen SM (2016) Validation of the cepstral spectral index of dysphonia (CSID) as a screening tool for voice disorders: development of clinical cutoff scores. J Voice 30:130–144.  https://doi.org/10.1016/j.jvoice.2015.04.009 CrossRefPubMedGoogle Scholar
  14. 14.
    Maryn Y, De Bodt M, Barsties B, Roy N (2014) The value of the acoustic voice quality index as a measure of dysphonia severity in subjects speaking different languages. Eur Arch Otorhinolaryngol 271:1609–1619.  https://doi.org/10.1007/s00405-013-2730-7 PubMedGoogle Scholar
  15. 15.
    Barsties B, Maryn Y The improvement of internal consistency of the Acoustic Voice Quality Index. Am J Otolaryngol 36:647–656.  https://doi.org/10.1016/j.amjoto.2015.04.012
  16. 16.
    Barsties B, Maryn Y (2012) The Acoustic Voice Quality Index. Toward expanded measurement of dysphonia severity in German subjects. HNO 60:715–720.  https://doi.org/10.1007/s00106-012-2499-9 CrossRefPubMedGoogle Scholar
  17. 17.
    Reynolds V, Buckland A, Bailey J et al (2012) Objective assessment of pediatric voice disorders with the acoustic voice quality index. J Voice 26:672.e1–672.e7.  https://doi.org/10.1016/j.jvoice.2012.02.002 CrossRefGoogle Scholar
  18. 18.
    Uloza V, Petrauskas T, Padervinskis E et al (2017) Validation of the Acoustic Voice Quality Index in the Lithuanian language. J Voice 31:257.e1–257.e11.  https://doi.org/10.1016/j.jvoice.2016.06.002 CrossRefGoogle Scholar
  19. 19.
    Kankare E, Barsties B, Maryn Y, Ilomäki I, Laukkanen AM, Tyrmi J, Rantala L, Asikainen M, Rorarius E, Siirilä MVS (2015) A preliminary study of the Acoustic Voice Quality Index in Finnish speaking population. A Prelim. study Acoust. Voice Qual. Index Finnish Speak. Popul. 11th Pan European Voice Conference; 2015 August 31th–September 4th. Florence, p 218Google Scholar
  20. 20.
    Maryn Y, Kim H-T, Kim J (2016) Auditory-perceptual and acoustic methods in measuring dysphonia severity of Korean speech. J Voice 30:587–594.  https://doi.org/10.1016/j.jvoice.2015.06.011 CrossRefPubMedGoogle Scholar
  21. 21.
    Hosokawa K, Barsties B, Iwahashi T et al (2017) Validation of the Acoustic Voice Quality Index in the Japanese Language. J Voice 31:260.e1–260.e9.  https://doi.org/10.1016/j.jvoice.2016.05.010 CrossRefGoogle Scholar
  22. 22.
    Maryn Y, Weenink D (2015) Objective dysphonia measures in the program Praat: smoothed cepstral peak prominence and Acoustic Voice Quality Index. J Voice 29:35–43.  https://doi.org/10.1016/j.jvoice.2014.06.015 CrossRefPubMedGoogle Scholar
  23. 23.
    Deliyski DD, Shaw HS, Evans MK (2005) Adverse effects of environmental noise on acoustic voice quality measurements. J Voice 19:15–28.  https://doi.org/10.1016/j.jvoice.2004.07.003 CrossRefPubMedGoogle Scholar
  24. 24.
    Dejonckere PH, Bradley P, Clemente P et al (2001) A basic protocol for functional assessment of voice pathology, especially for investigating the efficacy of (phonosurgical) treatments and evaluating new assessment techniques. Guideline elaborated by the Committee on Phoniatrics of the European Laryngolo. Eur Arch Otorhinolaryngol 258:77–82CrossRefPubMedGoogle Scholar
  25. 25.
    Kempster GB, Gerratt BR, Verdolini Abbott K et al (2009) Consensus auditory-perceptual evaluation of voice: development of a standardized clinical protocol. Am J Speech Lang Pathol 18:124–132.  https://doi.org/10.1044/1058-0360(2008/08-0017)CrossRefPubMedGoogle Scholar
  26. 26.
    Martins PC, Couto TE, Gama ACC (2015) Auditory-perceptual evaluation of the degree of vocal deviation: correlation between the visual analogue scale and numerical scale. CoDAS 27:279–284.  https://doi.org/10.1590/2317-1782/20152014167 CrossRefPubMedGoogle Scholar
  27. 27.
    Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37–46.  https://doi.org/10.1177/001316446002000104 CrossRefGoogle Scholar
  28. 28.
    Fleiss JL (1971) Measuring nominal scale agreement among many raters. Psychol Bull 76:378–382.  https://doi.org/10.1037/h0031619 CrossRefGoogle Scholar
  29. 29.
    Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174CrossRefPubMedGoogle Scholar
  30. 30.
    Portney LG, Watkins M (2000) Foundations of clinical research: applications to practice (vol 2)Google Scholar
  31. 31.
    Van Belle S, Albert A (2009) Agreement between two independent groups of raters. Psychometrika 74:477–491.  https://doi.org/10.1007/S11336-009-9116-1 CrossRefGoogle Scholar
  32. 32.
    Frey LR, Botan CH, Friedman PG, Kreps GL (1991) Investigating communication: an introduction to research methods, 1st edn. Prentice Hall, New JerseyGoogle Scholar
  33. 33.
    Sheskin D (2000) Handbook of parametric and nonparametric statistical procedures, vol 972. CRC Press, Boca Raton.  https://doi.org/10.2307/2685909 Google Scholar
  34. 34.
    Dollaghan CA (2007) The handbook for evidence-based practice in communication disorders. MD Brooks, BaltimoreGoogle Scholar
  35. 35.
    Ulozaite N, Petrauskas T, Saferis V, Uloza V (2016) Correlations between automated dysphonia quantification and perceptual voice evaluation. In: Biomed. Eng.—2016 Proc. 20th Int. Conf. Kaunas University of Technology. Lithuanian Society of Biomedical Engineering, Kaunas, pp 147–152Google Scholar
  36. 36.
    Awan SN, Miesemer SA, Nicolia TA (2012) An examination of intrasubject variability on the dysphonia severity index. J Voice.  https://doi.org/10.1016/j.jvoice.2012.04.004 Google Scholar
  37. 37.
    Jayakumar T, Savithri SR (2012) Effect of geographical and ethnic variation on Dysphonia Severity Index: a study of Indian population. J Voice.  https://doi.org/10.1016/j.jvoice.2010.05.008 PubMedGoogle Scholar
  38. 38.
    Maruthy S, Ravibabu P (2015) Comparison of Dysphonia Severity Index between younger and older carnatic classical singers and nonsingers. J Voice 29:65–70.  https://doi.org/10.1016/j.jvoice.2014.05.001 CrossRefPubMedGoogle Scholar
  39. 39.
    Young WG, Hoffman MR, Koszewski IJ et al (2016) Voice outcomes following a single office-based steroid injection for vocal fold scar. Otolaryngol Head Neck Surg 155:820–828.  https://doi.org/10.1177/0194599816654899 CrossRefPubMedGoogle Scholar
  40. 40.
    Meister J, Hagen R, Shehata-Dieler W et al (2017) Pitch elevation in male-to-female transgender persons-the Wurzburg approach. J Voice 31:244.e7–244.e15.  https://doi.org/10.1016/j.jvoice.2016.07.018 CrossRefGoogle Scholar
  41. 41.
    Lee JC, Breen D, Scott A et al (2016) Quantitative study of voice dysfunction after thyroidectomy. Surgery 160:1576–1581.  https://doi.org/10.1016/j.surg.2016.07.015 CrossRefPubMedGoogle Scholar
  42. 42.
    Hakkesteegt MM, Wieringa MH, Brocaar MP et al (2008) The interobserver and test-retest variability of the dysphonia severity index. Folia Phoniatr Logop 60:86–90.  https://doi.org/10.1159/000114650 CrossRefPubMedGoogle Scholar
  43. 43.
    Hakkesteegt MM, Brocaar MP, Wieringa MH, Feenstra L (2008) The relationship between perceptual evaluation and objective multiparametric evaluation of dysphonia severity. J Voice 22:138–145.  https://doi.org/10.1016/j.jvoice.2006.09.010 CrossRefPubMedGoogle Scholar
  44. 44.
    Maryn Y, Morsomme D, De Bodt M (2017) Measuring the Dysphonia Severity Index (DSI) in the program Praat. J Voice.  https://doi.org/10.1016/j.jvoice.2017.01.002 Google Scholar
  45. 45.
    Lee JM, Roy N, Peterson E, Merrill RM (2017) Comparison of two multiparameter acoustic indices of dysphonia severity: the Acoustic Voice Quality Index and Cepstral Spectral Index of dysphonia. J Voice.  https://doi.org/10.1016/j.jvoice.2017.06.012 Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of OtolaryngologyLithuanian University of Health SciencesKaunasLithuania
  2. 2.Faculty of Medicine and Health SciencesUniversity of AntwerpAntwerpBelgium
  3. 3.Institute of Health StudiesHAN University of Applied SciencesNijmegenThe Netherlands
  4. 4.European Institute for ORLSint-Augustinus HospitalAntwerpBelgium
  5. 5.Department of Speech, Language and Hearing SciencesGhent UniversityGhentBelgium
  6. 6.Faculty of Education, Health & Social WorkUniversity College GhentGhentBelgium

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