Validation of the Acoustic Voice Quality Index, Version 03.01, in French

[en] Objectives: The Acoustic Voice Quality Index (AVQI), version 03.01, is a tool for quantitative assessment of the overall severity of dysphonia. It is based on the recordings of a sustained vowel and part of a text read aloud. For the Dutch sample, 34 syllables must be read aloud to balance the duration of the two tasks. The first part of this study thus aimed to determine how many syllables of a commonly used text in the French-speaking part of Belgium should be used to achieve the same balance. The psychometric qualities of the AVQI have been confirmed by numerous publications in various languages. However, its validation in French relies on a small cohort of patients, who were not native French speakers. Furthermore, version 03.01 of the AVQI has not yet been validated at all on French samples. Hence, the main aim of this study was to assess the criterion-related concurrent validity and diagnostic accuracy of the AVQI 03.01 applied to a sample of native French speakers. Methods: For the first part of this study, the optimal part of the text to be used for the AVQI was identified, taking into account both its phonemic contents and its time balance with the sustained vowel. For the validation study, 90 recordings from the University Hospital of Liège's ENT caseload database were used, as well as 30 new recordings of normophonic individuals, composing a control group. Four judges assessed the recordings using the G parameter of the GRBAS scale. Once the intra- and inter-rater reliability of the perceptual ratings was confirmed, the AVQI 03.01's criterion validity was assessed on the French sample. The diagnostic accuracy of the AVQI 03.01 in French was measured, and the cut-off score allowing for the greatest diagnostic precision determined. Results: The most appropriate syllable number of the text to be read aloud was found to be 27, in order to balance the time analyzed for both the sustained vowel and the continuous speech. Regarding the validation study, intra-rater reliability was substantial for each of the four vocologists (κmean =.778, P < 0.0001), and inter-rater reliability was high (W =.895, P < 0.0001). The Spearman correlation between the perceptual judgments and the AVQI 03.01 score was strong (rs =.84, P < 0.0001). The receiver operating characteristic-curve parameters indicated that the ideal cut-off score allowing for the highest diagnostic accuracy of the AVQI, version 03.01, applied to a French sample is 2.33, with a sensitivity of 59.8%, a specificity of 100%, an infinite positive likelihood ratio (LR+) and a negative likelihood ratio (LR−) of 0.4. Conclusions: This study confirms the external validity of the AVQI 03.01 when applied on a French 27-syllable sample. The AVQI 03.01 is a robust, ecologically valid objective measure of overall voice quality. The cut-off score to be used is 2.33. However, clinicians should be cautious when the AVQI score is lower than 2.33. The AVQI 03.01 does not yield a sufficiently low negative likelihood ratio to be sure that this score indeed indicates normophonia. Also, taking into account the limitations regarding the perceptual judgements used in this study, a replication study should be carried out in order to confirm the cut-off score. © 2018 Elsevier Ltd

Disciplines :

Otolaryngology

Author, co-author :

Pommée, Timothy; Faculté de Psychologie, Logopédie et Sciences de l'Education, Unité de Logopédie des Troubles de la Voix, University of Liège, Belgium

Maryn, Youri; Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium, European Institute for ORL, Sint-Augustinus Hospital, Antwerp, Belgium, Department of Speech, Language and Hearing Sciences, Ghent University, Ghent, Belgium, Faculty of Education, Health and Social Work, University College Ghent, Belgium

Finck, Camille ; Université de Liège - ULiège > Département des sciences cliniques > Phoniatrie

Morsomme, Dominique ; Université de Liège - ULiège > Département de Logopédie > Logopédie des troubles de la voix

Language :

English

Title :

Validation of the Acoustic Voice Quality Index, Version 03.01, in French

Publication date :

2018

Journal title :

Journal of Voice

ISSN :

0892-1997

eISSN :

1873-4588

Publisher :

Mosby Inc.

Volume :

Issue :

Pages :

646.e11−646.e26

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 11 January 2019

Statistics

Number of views

69 (8 by ULiège)

Number of downloads

1 (1 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

Bibliography

Maryn, Y, Corthals, P, Van Cauwenberge, P, et al. Toward improved ecological validity in the acoustic measurement of overall voice quality: combining continuous speech and sustained vowels. J Voice 24 (2009), 540–555 https://doi.org/10.1016/j.jvoice.2008.12.014.
Dejonckere, PH, Bradley, P, Clemente, P, et al. 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 Laryngological Society (ELS). Eur Arch Otorhinolaryngol 258 (2001), 77–82 https://doi.org/10.1007/s004050000299.
Wuyts, FL, De Bodt, M, Molenberghs, G, et al. The Dysphonia Severity Index: an objective measure of vocal quality based on a multiparameter approach. J Speech Lang Hear Res 43 (2000), 796–809 https://doi.org/10.1044/jslhr.4303.796.
Hirano, M., Psycho-acoustic evaluation of voice: GRBAS scale for evaluating the hoarse voice. 1981, Springer Verlag, Wien.
Jacobson, B, Johnson, A, Grywalski, C, et al. The Voice Handicap Index (VHI): development and validation. Am J Speech Lang Pathol 6 (1997), 66–69 https://doi.org/10.1044/1058-0360.0603.66.
Verduyckt, I, Remacle, M, Jamart, J, et al. Voice-related complaints in the pediatric population. J Voice 25 (2011), 373–380 https://doi.org/10.1016/j.jvoice.2009.11.008.
Maryn, Y, Weenink, D, Objective dysphonia measures in the program Praat: smoothed cepstral peak prominence and Acoustic Voice Quality Index. J Voice 29 (2015), 35–43 https://doi.org/10.1016/j.jvoice.2014.06.015.
Heman-Ackah, YD, Heuer, RJ, Michael, DD, et al. Cepstral peak prominence: a more reliable measure of dysphonia. Ann Otol Rhinol Laryngol 112 (2003), 324–333 https://doi.org/10.1177/000348940311200406.
Ferrer, C, De Bodt, M, Maryn, Y, et al. Properties of the cepstral peak prominence and its usefulness in vocal quality measurements. In: 5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, 2007, Firenze University Press, Florence, 93–96.
Hillenbrand, JM, A methodological study of perturbation and additive noise in synthetically generated voice signals. J Speech Hearing Res 30 (1987), 448–461 https://doi.org/10.1044/jshr.3004.448.
Schoentgen, J, Spectral models of additive and modulation noise in speech and phonatory excitation signals. J Acoust Soc Am 113 (2003), 553–562 https://doi.org/10.1121/1.1523384.
Autesserre, D, Charpy, N, Crevier-Buchman, L, et al. La voix: Ses troubles chez les enseignants. 2006, Les éditions INSERM, Paris.
Delgado, J, León, N, Izquierdo, L, et al. Cepstral analysis of normal and pathological voice in Spanish adults. Smoothed cepstral peak prominence in sustained vowels versus connected speech. Acta Otorrinolaringol Esp 69 (2018), 134–140 https://doi.org/10.1016/j.otorri.2017.05.006.
Lowell, S, Colton, R, Kelley, R, et al. Spectral- and cepstral-based measures during continuous speech: capacity to distinguish dysphonia and consistency within a speaker. J Voice 25 (2011), e223–e232 https://doi.org/10.1016/j.jvoice.2010.06.007.
Sauder, C, Bretl, M, Eadie, T, Predicting voice disorder status from smoothed measures of cepstral peak prominence using Praat and Analysis of Dysphonia in Speech and Voice (ADSV). J Voice 31 (2017), 557–566 https://doi.org/10.1016/j.jvoice.2017.01.006.
Barsties, B, Maryn, Y, Test-retest-variabilität und interne Konsistenz des Acoustic Voice Quality Index. HNO 61 (2013), 399–403 https://doi.org/10.1007/s00106-012-2649-0.
Barsties, B, Ulozaite-Staniene, N, Maryn, Y, et al. The influence of gender and age on the Acoustic Voice Quality Index and Dysphonia Severity Index: a normative study. J Voice, 2017 https://doi.org/10.1016/j.jvoice.2017.11.011.
Hakkesteegt, M, Brocaar, M, Wieringa, M, et al. Influence of age and gender on the Dysphonia Severity Index: a study of normative values. Folia Phoniatr Logop 58 (2006), 264–273 https://doi.org/10.1159/000093183.
Barsties, B, Maryn, Y, External validation of the Acoustic Voice Quality Index version 03.01 with extended representativity. Ann Otol Rhinol Laryngol 125 (2016), 571–583 https://doi.org/10.1177/0003489416636131.
Maryn, Y, De Bodt, M, Roy, N, The Acoustic Voice Quality Index: toward improved treatment outcomes assessment in voice disorders. J Commun Disord 43 (2010), 161–174 https://doi.org/10.1016/j.jcomdis.2009.12.004.
Maryn, Y, De Bodt, M, Barsties, B, et al. The value of the Acoustic Voice Quality Index as a measure of dysphonia severity in subjects speaking different languages. Eur Arch Otorhinolaryngol 271 (2014), 1609–1619 https://doi.org/10.1007/s00405-013-2730-7.
Reynolds, V, Buckland, A, Bailey, J, et al. Objective assessment of pediatric voice disorders with the Acoustic Voice Quality Index. J Voice 26 (2012), 672.e1–672.e7 https://doi.org/10.1016/j.jvoice.2012.02.002.
Barsties, B, Maryn, Y, Der Acoustic Voice Quality Index in Deutsch: ein Messverfahren zur allgemeinen Stimmqualität. HNO 60 (2012), 715–720 https://doi.org/10.1007/s00106-012-2499-9.
Hosokawa, K, Barsties, B, Iwahashi, T, et al. Validation of the Acoustic Voice Quality Index in the Japanese language. J Voice 31 (2017), 260.e1–260.e9 https://doi.org/10.1016/j.jvoice.2016.05.010.
Hosokawa, K, Barsties, B, Iwahashi, T, et al. The Acoustic Voice Quality Index version 03.01 for the Japanese-speaking population. J Voice, 2017 https://doi.org/10.1016/j.jvoice.2017.10.003.
Kankare, E, Barsties, B, Maryn, Y, et al. A preliminary study of the Acoustic Voice Quality Index in Finnish speaking population. Paper presented at the 11th Pan-European Voice Conference, Florence, Italy, 2015.
Maryn, Y, Kim, H-T, Kim, J, Auditory-perceptual and acoustic methods in measuring dysphonia severity of Korean speech. J Voice 30 (2016), 587–594 https://doi.org/10.1016/j.jvoice.2015.06.011.
Uloza, V, Petrauskas, T, Padervinskis, E, et al. Validation of the Acoustic Voice Quality Index in the Lithuanian language. J Voice 31 (2017), 257.e1–257.e11 https://doi.org/10.1016/j.jvoice.2016.06.002.
Uloza, V, Barsties, B, Ulozaite, N, et al. A comparison of Dysphonia Severity Index and Acoustic Voice Quality Index measures in differentiating normal and dysphonic voices. Eur Arch Otorhinolaryngol 275 (2018), 949–958 https://doi.org/10.1007/s00405-018-4903-x.
Delgado, J, Gómez, L, Jiménez, A, et al. Validation of the Acoustic Voice Quality Index version 03.01 and the Acoustic Breathiness Index in the Spanish language. Ann Otol Rhinol Laryngol 127 (2018), 317–326 https://doi.org/10.1177/0003489418761096.
Barsties, B, Maryn, Y, The improvement of the internal consistency of the Acoustic Voice Quality Index. Am J Otolaryngol 36 (2015), 647–656 https://doi.org/10.1016/j.amjoto.2015.04.012.
Barsties, B, Maryn, Y, The influence of voice sample length in the auditory-perceptual judgment of overall voice quality. J Voice 31 (2017), 202–210 https://doi.org/10.1016/j.jvoice.2016.07.006.
Remacle, A, Petitfils, C, Finck, C, et al. Description of patients consulting the voice clinic regarding gender, age, occupational status, and diagnosis. Eur Arch Otorhinolaryngol 274 (2017), 1567–1576 https://doi.org/10.1007/s00405-016-4332-7.
Harmegnies, B, Landercy, A, Intra-speaker variability of the long-term speech spectrum. Speech Commun 7 (1988), 81–86 https://doi.org/10.1016/0167-6393(88)90023-4.
Tubach, J, Boe, L., Un corpus de transcription phonétique (300000 phones): Constitution et exploitation statistique. 1990, École nationale supérieure des télécommunications, Paris.
Andale. Fisher Z-Transformation. 2016 Accessed March 11, 2017 Available at http://www.statisticshowto.com/fisher-z/.
Kenny, DA., Statistics for the Social and Behavioral Sciences. 1987, Little, Brown and Company, Boston.
Belgian National Institute for Health and Disability Insurance. Code éthique et déontologique des logopèdes. 2014 Available at http://www.inami.fgov.be/fr/professionnels/sante/logopedes-code-ethique-deontologique.aspx.
Chial, MR., Suggestions for Computer-Based Audio Recording of Speech Samples for Perceptual and Acoustic Analyses. 2003, University of Wisconsin-Madison, Madison, WI.
Ikuma, T, Kunduk, M, Fink, D, et al. A spatiotemporal approach to the objective analysis of initiation and termination of vocal-fold oscillation with high-speed videoendoscopy. J Voice 30 (2016), 756.e21–756.e30 https://doi.org/10.1016/j.jvoice.2015.09.007.
Schaeffler, F, Beck, J, Jannetts, S, Phonation stabilisation time as an indicator of voice disorder. Proceedings of the 18th International Congress of Phonetic Sciences (ICPhS), 2015, International Phonetic Association, Glasgow, Scotland Available at https://www.internationalphoneticassociation.org/icphs-proceedings/ICPhS2015/Papers/ICPHS0331.pdf.
Dollaghan, CA., The handbook for evidence-based practice in communication disorders. 2007, Brookes Publishing, Baltimore, MD.
Mayer, J., Praat Skripte: Sound-Objekte zusammenfügen. 2013 Accessed January 3, 2017, Available at: http://praatpfanne.lingphon.net/downloads/concatenateWithPause.txt.
Mayer, J., Praat Skripte: Auditive Stimmanalyse (GRBAS) mit dem Demo-Window. 2011 Accessed January 2, 2018, Available at: http://praatpfanne.lingphon.net/downloads/demo_GRBAS.txt.
Kreiman, J, Gerratt, BR, Kempster, GB, Erman, A, Berke, GS, Perceptual evaluation of voice quality: review, tutorial, and a framework for future research. J Speech Hearing Res 36 (1993), 21–40 https://doi.org/10.1044/jshr.3601.21.
Maltby, MA, Knight, P., Audiology: An Introduction for Teachers and Other Professionals. 2015, Routledge, New York.
American Speech-Language-Hearing Association. Adult Hearing Screening. 2017 Accessed March 10, 2018, Available at: https://www.asha.org/PRPSpecificTopic.aspx?folderid=8589942721§ion= Key_Issues.
Awan, SN, Roy, N, Toward the development of an objective index of dysphonia severity: a four-factor acoustic model. Clin Linguist Phon 20 (2006), 35–49 https://doi.org/10.1080/02699200400008353.
Kreiman, J, Gerratt, BR, Precoda, K, et al. Individual differences in voice quality perception. J Speech Hearing Res 35 (1992), 512–520 https://doi.org/10.1044/jshr.3503.512.
Eadie, TL, Doyle, PC, Classification of dysphonic voice: acoustic and auditory-perceptual measures. J Voice 19 (2005), 1–14 https://doi.org/10.1016/j.jvoice.2004.02.002.
Maryn, Y, Roy, N, Sustained vowels and continuous speech in the auditory-perceptual evaluation of dysphonia severity. J Soc Bras Fonoaudiol 24 (2012), 107–112 https://doi.org/10.1590/S2179-64912012000200003.
Santos, F., Le kappa de Cohen: Un outil de mesure de l'accord interjuges sur des caractères qualitatifs. 2018 Available at http://www.pacea.u-bordeaux1.fr/IMG/pdf/Kappa_Cohen.pdf.
McHugh, M, Interrater reliability: the kappa statistic. Biochem Med (Zagreb) 22 (2012), 276–282 https://doi.org/10.11613/BM.2012.031.
Perinetti, G, StaTips Part III: assessment of the repeatability and rater agreement for nominal and ordinal data. S Eur J Orthod Dentofacial Res 4 (2017), 3–4 https://doi.org/10.5937/sejodr4-15199.
Portney, LG, Watkins, MP., Foundations of clinical research, applications to practice. 2nd ed, 2000, Prentice-Hall, Upper Saddle River, NJ.
Hart, P, Receiver Operating Characteristic (ROC) curve analysis: a tutorial using Body Mass Index (BMI) as a measure of obesity. J Phys Activ Res 1 (2016), 5–8 https://doi.org/10.12691/jpar-1-1-2.
Ruopp, MD, Perkins, NJ, Whitcomb, BW, et al. Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection. Biom J 50 (2008), 419–430 https://doi.org/10.1002/bimj.200710415.
Habibzadeh, F, Habibzadeh, P, Yadollahie, M, On determining the most appropriate test cut-off value: the case of tests with continuous results. Biochemia Medica 26 (2016), 297–307 https://doi.org/10.11613/BM.2016.034.
Landis, JR., Koch, GG, The measurement of observer agreement for categorical data. Biometrics 33 (1977), 159–174 https://doi.org/10.2307/2529310.
Schmidt, RC, Managing delphi surveys using nonparametric statistical techniques. Decision Sciences 28 (1997), 763–774 https://doi.org/10.1111/j.1540-5915.1997.tb01330.x.
Cohen, J., Statistical Power Analysis for the Behavioral Sciences. (2nd ed.)., 1988, Erlbaum, Hillsdale, NJ.
Hinkle, D, Wiersma, W, Jurs, S, Applied Statistics for the Behavioral Sciences. (3rd ed.)., 1994, Houghton Mifflin, Boston.
Swets, JA, Measuring the accuracy of diagnostic systems. Science 240 (1988), 1285–1293 https://doi.org/10.1126/science.3287615.
Akobeng, AK, Understanding diagnostic tests 2: likelihood ratios, pre- and post-test probabilities and their use in clinical practice. Acta Paediatr 96 (2006), 487–491 https://doi.org/10.1111/j.1651-2227.2006.00179.x.
Awan, SN, Lawson, LL, The effect of anchor modality on the reliability of vocal severity ratings. J Voice 23 (2009), 341–352 https://doi.org/10.1016/j.jvoice.2007.10.006.
Brinca, L, Batista, AP, Tavares, AI, et al. The effect of anchors and training on the reliability of voice quality ratings for different types of speech stimuli. J Voice 29 (2015), 776.e7–776.e14 https://doi.org/10.1016/j.jvoice.2015.01.007.
Goldstone, RL, Perceptual learning. Ann Rev Psychol 49 (1998), 585–612.
Draugiem Group. The secret of the 10% most productive people? Breaking!. 2014 Accessed February 28, 2018, Available at: https://desktime.com/blog/17-52-ratio-most-productive-people/.
White, M., The exact perfect amount of time to take a break, according to data. 2014 Accessed February 28, 2018, Available at: http://time.com/3518053/perfect-break/.
Baken, RJ, Orlikoff, RF., Clinical Measurement of Speech and Voice. (2nd ed.)., 2000, Cengage Learning, Boston.