Advertisement

Comparison and Validation of Acoustic Voice Quality Index Version 2 and Version 3 among South Indian Population

  • T. Jayakumar
    Correspondence
    Address correspondence and reprint requests to T. Jayakumar, Associate Professor and Head, Department of Speech-Language Sciences, All India Institute of Speech and Hearing, University of Mysore, Manasagangothri, Mysuru, Karnataka, India, 570006.
    Affiliations
    Associate Professor of Speech Sciences, Department of Speech-Language Sciences, All India Institute of Speech and Hearing, University of Mysore, Mysuru, Karnataka, India
    Search for articles by this author
  • R. Rajasudhakar
    Affiliations
    Associate Professor of Speech Sciences, Department of Speech-Language Sciences, All India Institute of Speech and Hearing, University of Mysore, Mysuru, Karnataka, India
    Search for articles by this author
  • Jesnu Jose Benoy
    Affiliations
    Junior Research Fellow, Department of Speech-Language Sciences, All India Institute of Speech and Hearing, University of Mysore, Mysuru, Karnataka, India
    Search for articles by this author

      Summary

      Background

      Acoustic Voice Quality Index (AVQI) has emerged in the recent past as a robust multiparametric voice quality evaluation tool. Two versions of AVQI derived using the program PRAAT have found extensive clinical and research applications. These versions have been validated in several languages around the world. However, no research reports are available on validation of AVQI in the South Indian population. Further, studies comparing the performance of the two versions of AVQI are limited in the literature.

      Objectives

      This study was designed to validate and compare the two versions of AVQI (AVQIv02.02 and AVQIv03.01) in South Indian languages (Malayalam and Kannada).

      Methods

      A retrospective analysis of previously recorded voice samples was carried out on a total of 160 (91 normophonic and 69 dysphonic) voice samples. These samples were perceptually rated on a GRBAS scale by five experienced speech-language pathologists. Standardized Syllable Number (SSN) necessary to derive AVQIv03.01 was computed. Following this, these samples were analyzed to obtain the AVQIv02.02 and AVQIv03.01. The concurrent validity and diagnostic accuracy of these measures were then examined and compared.

      Results

      A moderate agreement was obtained across the judges on perceptual evaluation of voice quality. SSN in Malayalam and Kannada languages were identified to be 29 and 25 syllables respectively. Language differences were not observed on both versions of AVQI. The concurrent validity of AVQIv03.01 (r = 0.788) was superior to that of AVQIv02.02 (r = 0.655). Further, the threshold of differentiating normophonic and dysphonic samples were determined to be >3.45 for AVQIv02.02 and >2.45 for AVQIv03.01.

      Conclusions

      AVQIv03.01 is superior to AVQIv02.02 in terms of its diagnostic accuracy and concurrent validity. Current findings also extend the application of AVQI as a robust tool for the evaluation of voice characteristics to the South Indian population.

      Key Words

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of Voice
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Jesus LMT
        • Castilho S
        • Alves M
        • et al.
        An open access standardised voice evaluation protocol.
        J Voice. 2021; (Published online October)https://doi.org/10.1016/j.jvoice.2021.09.010
        • 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.
        Eur Arch Oto-Rhino-L. 2001; 258: 77-82https://doi.org/10.1007/s004050000299
        • Patel RR
        • Awan SN
        • Barkmeier-Kraemer J
        • 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-Lang Pathol. 2018; 27: 887-905https://doi.org/10.1044/2018_AJSLP-17-0009
        • Boominathan P
        • Samuel J
        • Arunachalam R
        • et al.
        Multi parametric voice assessment: sri ramachandra university protocol.
        Indian J Otolaryngol Head Neck Surg. 2014; 66: 246-251https://doi.org/10.1007/s12070-011-0460-y
        • Barsties B
        • de Bodt M.
        Assessment of voice quality: Current state-of-the-art.
        Auris Nasus Larynx. 2015; 42: 183-188https://doi.org/10.1016/j.anl.2014.11.001
        • Maryn Y
        • Roy N
        • de Bodt M
        • et al.
        Acoustic measurement of overall voice quality: A meta-analysis.
        J Acoust Soc Am. 2009; 126: 2619-2634https://doi.org/10.1121/1.3224706
        • 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. 2010; 24: 540-555https://doi.org/10.1016/j.jvoice.2008.12.014
        • Awan SN
        • Solomon NP
        • Helou LB
        • et al.
        Spectral-cepstral estimation of dysphonia severity: external validation.
        Ann Otol, Rhinol Laryngol. 2013; 122https://doi.org/10.1177/000348941312200108
        • Awan SN
        • Roy N
        • Zhang D
        • et al.
        Validation of the cepstral spectral index of dysphonia (CSID) as a screening tool for voice disorders: development of clinical cutoff scores.
        J Voice. 2016; 30: 130-144https://doi.org/10.1016/j.jvoice.2015.04.009
        • Wuyts FL
        • Bodt MS de
        • Molenberghs G
        • et al.
        The dysphonia severity index.
        J Speech, Lang Hearing Res. 2000; 43: 796-809https://doi.org/10.1044/jslhr.4303.796
        • Maryn Y
        • Weenink D.
        Objective dysphonia measures in the program praat: smoothed cepstral peak prominence and acoustic voice quality index.
        J Voice. 2015; 29: 35-43https://doi.org/10.1016/j.jvoice.2014.06.015
        • Hosokawa K
        • Barsties B
        • Iwahashi T
        • et al.
        Validation of the acoustic voice quality index in the japanese language.
        J Voice. 2017; 31: 260.e1-260.e9https://doi.org/10.1016/j.jvoice.2016.05.010
        • Kankare E
        • Barsties V.
        • Latoszek B
        • et al.
        The acoustic voice quality index version 02.02 in the Finnish-speaking population.
        Logoped Phoniatr Vocol. 2020; 45: 49-56https://doi.org/10.1080/14015439.2018.1556332
        • Kim GH
        • Lee YW
        • Bae IH
        • et al.
        Validation of the acoustic voice quality index in the Korean language.
        J Voice. 2019; 33: 948.e1-948.e9https://doi.org/10.1016/j.jvoice.2018.06.007
        • Uloza V
        • Petrauskas T
        • Padervinskis E
        • et al.
        Validation of the acoustic voice quality index in the lithuanian language.
        J Voice. 2017; 31: 257.e1-257.e11https://doi.org/10.1016/j.jvoice.2016.06.002
        • Yeşilli-Puzella G
        • Tadıhan-Özkan E
        • Maryn Y.
        Validation and test-retest reliability of acoustic voice quality index version 02.06 in the Turkish language.
        J Voice. 2020; (Published online September)https://doi.org/10.1016/j.jvoice.2020.08.021
        • Barsties B
        • Maryn Y.
        The improvement of internal consistency of the acoustic voice quality index.
        Am J Otolaryngol. 2015; 36: 647-656https://doi.org/10.1016/j.amjoto.2015.04.012
        • Barsties B
        • Maryn Y.
        External validation of the acoustic voice quality index version 03.01 with extended representativity.
        Ann Otolo Rhinol Laryngol. 2016; 125: 571-583https://doi.org/10.1177/0003489416636131
        • Kim GH
        • von Latoszek BB
        • Lee YW.
        Validation of acoustic voice quality index version 3.01 and acoustic breathiness index in korean population.
        J Voice. 2021; 35: 660.e9-660.e18https://doi.org/10.1016/j.jvoice.2019.10.005
        • Hosokawa K
        • Barsties v Latoszek B
        • Iwahashi T
        • et al.
        The acoustic voice quality index version 03.01 for the Japanese-speaking population.
        J Voice. 2019; 33: 125.e1-125.e12https://doi.org/10.1016/j.jvoice.2017.10.003
        • Delgado Hernández J
        • León Gómez NM
        • 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. 2018; 127: 317-326https://doi.org/10.1177/0003489418761096
        • Barsties v. Latoszek B
        • Lehnert B
        • Janotte B.
        Validation of the acoustic voice quality index version 03.01 and acoustic breathiness index in German.
        J Voice. 2020; 34: 157.e17-157.e25https://doi.org/10.1016/j.jvoice.2018.07.026
        • Fantini M
        • Ricci Maccarini A
        • Firino A
        • et al.
        Validation of the acoustic voice quality index (AVQI) version 03.01 in Italian.
        J Voice. 2021; (Published online)https://doi.org/10.1016/j.jvoice.2021.02.029
        • Englert M
        • Barsties v.
        • Latoszek B
        • et al.
        Validation of the acoustic voice quality index, version 03.01, to the Brazilian Portuguese language.
        J Voice. 2021; 35: 160.e15-160.e21https://doi.org/10.1016/j.jvoice.2019.07.024
        • Pommée T
        • Maryn Y
        • Finck C
        • et al.
        Validation of the acoustic voice quality index, version 03.01, in French.
        J Voice. 2020; 34: 646.e11-646.e26https://doi.org/10.1016/j.jvoice.2018.12.008
        • Jayakumar T
        • Savithri SR.
        Effect of geographical and ethnic variation on dysphonia severity index: a study of Indian population.
        J Voice. 2012; 26: e11-e16https://doi.org/10.1016/j.jvoice.2010.05.008
        • Jayakumar T
        • Benoy JJ
        • Yasin HM.
        Effect of age and gender on acoustic voice quality index across lifespan: a cross-sectional study in indian population.
        J Voice. 2020; (Published online)https://doi.org/10.1016/j.jvoice.2020.05.025
        • Kishore Pebbili G
        • Shabnam S
        • Pushpavathi M
        • et al.
        Diagnostic accuracy of acoustic voice quality index version 02.03 in discriminating across the perceptual degrees of dysphonia severity in Kannada language.
        J Voice. 2021; 35: 159.e11-159.e18https://doi.org/10.1016/j.jvoice.2019.07.010
        • Kim GH
        • Lee YW
        • Bae IH
        • et al.
        Comparison of two versions of the acoustic voice quality index for quantification of dysphonia severity.
        J Voice. 2020; 34: 489.e11-489.e19https://doi.org/10.1016/j.jvoice.2018.11.013
        • Tsimpli IM
        • Vogelzang M
        • Balasubramanian A
        • et al.
        Linguistic diversity, multilingualism, and cognitive skills: a study of disadvantaged children in India.
        Languages. 2020; 5: 10https://doi.org/10.3390/languages5010010
        • Deliyski DD
        • Shaw HS
        • Evans MK.
        Adverse effects of environmental noise on acoustic voice quality measurements.
        J Voice. 2005; 19: 15-28https://doi.org/10.1016/j.jvoice.2004.07.003
        • Boersma P.
        PRAAT, a system for doing phonetics by computer.
        Glot International. 2001; 5: 341-345
      1. Mayer J. Praat script resources: GRBAS voice quality assessment. Published 2011. Accessed July 7, 2021. https://praatpfanne.lingphon.net/downloads/demo_GRBAS.txt

        • Kreiman J
        • Gerratt BR
        • Kempster GB
        • et al.
        Perceptual evaluation of voice quality: review, tutorial, and a framework for future research.
        J Speech, Lang Hearing Res. 1993; 36: 21-40https://doi.org/10.1044/jshr.3601.21
        • 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. 2008; 50: 419-430https://doi.org/10.1002/bimj.200710415
        • Akobeng AK.
        Understanding diagnostic tests 2: likelihood ratios, pre- and post-test probabilities and their use in clinical practice.
        Acta Paediatrica. 2007; 96: 487-491https://doi.org/10.1111/j.1651-2227.2006.00179.x
        • Landis JR
        • Koch GG.
        The measurement of observer agreement for categorical data.
        Biometrics. 1977; 33: 159-174
        • Koolagudi SG
        • Bharadwaj A
        • Srinivasa Murthy Y v
        • et al.
        Dravidian language classification from speech signal using spectral and prosodic features.
        Int J Speech Technol. 2017; 20: 1005-1016https://doi.org/10.1007/s10772-017-9466-5
        • Sengupta D
        • Saha G.
        Study on Similarity among Indian Languages Using Language Verification Framework.
        Adv Artificial Intelligence. 2015; 2015: 1-24https://doi.org/10.1155/2015/325703
        • Savithri SR
        • Jayaram M.
        Rate of speech/reading in Dravidian languages.
        J All India Institute Speech Hear. 2008; 27: 29-39
        • 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.
        Euro Arch Oto-Rhino-Laryngol. 2013; 271: 1609-1619https://doi.org/10.1007/s00405-013-2730-7
        • Barsties B
        • Maryn Y.
        The acoustic voice quality index. Toward expanded measurement of dysphonia severity in German subjects.
        HNO. 2012; 60: 715-720https://doi.org/10.1007/s00106-012-2499-9
        • Oates J.
        Auditory-perceptual evaluation of disordered voice quality.
        Folia Phoniatrica et Logopaedica. 2009; 61: 49-56https://doi.org/10.1159/000200768
        • Kreiman J
        • Gerratt BR.
        Sources of listener disagreement in voice quality assessment.
        J Acoust Soc Am. 2000; 108: 1867-1876https://doi.org/10.1121/1.1289362
        • Eadie TL
        • Baylor CR.
        The effect of perceptual training on inexperienced listeners’ judgments of dysphonic voice.
        J Voice. 2006; 20: 527-544https://doi.org/10.1016/j.jvoice.2005.08.007
        • Yiu EML
        • Murdoch B
        • Hird K
        • et al.
        Perception of synthesized voice quality in connected speech by Cantonese speakers.
        J Acoust Soc Am. 2002; 112: 1091-1101https://doi.org/10.1121/1.1500753
        • Schober P
        • Boer C
        • Schwarte LA.
        Correlation coefficients.
        Anesth Analges. 2018; 126: 1763-1768https://doi.org/10.1213/ANE.0000000000002864
        • Shrivastav R
        • Sapienza CM
        • Nandur V.
        Application of psychometric theory to the measurement of voice quality using rating scales.
        J Speech, Lang Hearing Res. 2005; 48: 323-335https://doi.org/10.1044/1092-4388(2005/022