Acoustic Parameters in the Evaluation of Voice Quality of Choral Singers. Prototype of Mobile Application for Voice Quality Evaluation

• Autorzy: Szklanny Krzysztof

Identyfikatory

DOI

10.24425/aoa.2019.129257

• Języki publikacji: EN

Abstrakty

EN

Choral singers are among intensive voice users whose excessive vocal effort puts them at risk of developing voice disorders. The aim of the work was to assess voice quality for choral singers in the choir at the Polish-Japanese Academy of Information Technology. This evaluation was carried out using the acoustic parameters from the COVAREP (A Collaborative Voice Analysis Repository For Speech Technologies) repository. A prototype of a mobile application was also prepared to allow the calculation of these parameters. The study group comprised 6 male and 19 female choir singers. The control group consisted of health non-singing individuals, 50 men and 39 women. Auditory perceptual assessment (using the RBH scale) as well as acoustic analysis were used to test the voice quality of all the participants. The voice quality of the female choir singers proved to be normal in comparison with the control group. The male choir singers were found to have tense voice in comparison with the controls. The parameters which proved most effective for voice evaluation were Peak Slope and Normalized Amplitude Quotient.

Słowa kluczowe

EN

web application; voice analysis; voice quality; acoustic analysis; COVAREP

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2019
• Tom: Vol. 44, No. 3
• Strony: 439--446
• Opis fizyczny: Bibliogr. 45 poz., tab.

Twórcy

autor

Szklanny Krzysztof

• Multimedia Department, Polish-Japanese Academy of Information Technology, Koszykowa 86, 02-008 Warsaw, Poland

Bibliografia

• 1. Alku P. (2011), Glottal inverse filtering analysis of human voice production – A review of estimation and parameterization methods of the glottal excitation and their applications, Sadhana – Academy Proceedings in Engineering Sciences, 36, 5, 623-650, https://doi.org/10.1007/s12046-011-0041-5.
• 2. Alku P., Bäckström T., Vilkman E. (2002), Normalized amplitude quotient for parametrization of the glottal flow, The Journal of the Acoustical Society of America, 112, 2, 701-710, https://doi.org/10.1121/1.1490365.
• 3. Alku P., Strik H., Vilkman E. (1997), Parabolic spectral parameter – A new method for quantification of the glottal flow, Speech Communication, 22, 1, 67-79, https://doi.org/10.1016/S0167-6393(97)00020-4.
• 4. Bäckström T., Alku P., Vilkman E. (2002), Time-domain parameterization of the closing phase of glottal airflow waveform from voices over a large intensity range, IEEE Transactions on Speech and Audio Processing, 10, 3, 186-192, https://doi.org/10.1109/TSA.2002.1001983.
• 5. Behlau M., Oliveira G. (2009), Vocal hygiene for the voice professional, Current Opinion in Otolaryngology and Head and Neck Surgery, https://doi.org/10.1097/MOO.0b013e32832af105.
• 6. Beiwinkel T. et al. (2016), Using smartphones to monitor bipolar disorder symptoms: a pilot study, JMIR Mental Health, 3, 1, e2, https://doi.org/10.2196/mental.4560.
• 7. Björkner E., Sundberg J., Alku P. (2006), Subglottal pressure and normalized amplitude quotient variation in classically trained baritone singers, Logopedics Phoniatrics Vocology, 31, 4, 157-165, https://doi.org/10.1080/14015430600576055.
• 8. Braun-Janzen C., Zeine L. (2009), Singers’ interest and knowledge levels of vocal function and dysfunction: Survey findings, Journal of Voice, 23, 4, 470-483, https://doi.org/10.1016/j.jvoice.2008.01.001.
• 9. Buenosvinos C., Soronnellas Ch., Akbary K. (2017), Domain-Driven Design in PHP, Packt Publishing.
• 10. Childers D. G., Lee C. K. (1991), Vocal quality factors: Analysis, synthesis, and perception, The Journal of the Acoustical Society of America, 90, 5, 2394-2410, https://doi.org/10.1121/1.402044.
• 11. Corona S. (2014), Scaling PHP7 applications, Lean-pub.
• 12. Degottex G., Kane J., Drugman T., Raitio T., Scherer S. (2014), COVAREP – A collaborative voice analysis repository for speech technologies, [in:] Proceedings of ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, 4-9 May, Florence, Italy, https://doi.org/10.1109/ICASSP.2014.6853739.
• 13. Dejonckere P. H. 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 Laryngological Society (ELS), European Archives of Oto-Rhino-Laryngology, 258, 2, 77-82, https://doi.org/10.1007/s004050000299.
• 14. Dejonckere P. H., Crevier-Buchman L., Marie J. P., Moerman M., Remacle M., Woisard V. (2003), Implementation of the European Laryngological Society (ELS) basic protocol for assessing voice treatment effect, Revue de laryngologie-otologie-rhinologie, 124, 5, 279-283.
• 15. Gravenhorst F. et al. (2015), Mobile phones as medical devices in mental disorder treatment: an overview, Personal and Ubiquitous Computing, 19, 2, 335-353, https://doi.org/10.1007/s00779-014-0829-5.
• 16. Gundermann H. (1970), The professional dysphonia [in German: Die Berufsdysphonie], Thieme, Leipzig.
• 17. Hacki T. (1989), Classification of glottic functions by means of electroglottography [in German: Klassifizierung von Glottisfunktionen mit Hilfe der Elektroglottographie], Folia Phoniatrica, 41, 43-48, https://doi.org/10.1159/000265931.
• 18. Hillenbrand J., Cleveland R. A., Erickson R. L. (1994), Acoustic correlates of breathy vocal quality, Journal of Speech Language and Hearing Research, 37, 4, 769-778, https://doi.org/10.1044/jshr.3704.769.
• 19. Kane J., Gobl C. (2011), Identifying regions of nonmodal phonation using features of the wavelet transform, [in:] Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, pp. 177-180.
• 20. Kane J., Gobl C. (2013), Wavelet maxima dispersion for breathy to tense voice discrimination, IEEE Transactions on Audio, Speech and Language Processing, 22, 6, 1170-1179, https://doi.org/10.1109/TASL.2013.2245653.
• 21. Krasner G. E., Pope S. T. (1988), A description of the model-view-controller user interface paradigm in the Smalltalk-80 System, Journal of Object Oriented Programming, 1, 3, 26-49.
• 22. Marasek K. (1997), Electroglottographic Description of voice quality, Arbeitspapiere des Instituts für Maschinelle Sprachverarbeitung, 3, 2, Diss. Habilitationsschrift, Stuttgart.
• 23. Mat Baki M. et al. (2015), Reliability of OperaVOX against Multidimensional Voice Program (MDVP), Clinical Otolaryngology, 40, 22-28, https://doi.org/10.1111/coa.12313.
• 24. Miloff A., Marklund A., Carlbring P. (2015), The challenger app for social anxiety disorder: New advances in mobile psychological treatment, Internet Interventions, 2, 4, 382-391, https://doi.org/10.1016/j.invent.2015.08.001.
• 25. Nawka T., Anders L. C., Wendler J. (1994), The auditory assessment of hoarse voices according to the RBH system [in German: Die auditive Beurteilung heiserer Stimmen nach dem RBH-System], Sprache, Stimme, Gehör, 18, 130-133.
• 26. Nicholas J., Larsen M. E., Proudfoot J., Christensen H. (2015), Mobile apps for bipolar disorder: A systematic review of features and content quality, Journal of Medical Internet Research, 17, 8, e198, https://doi.org/10.2196/jmir.4581.
• 27. NIDOCD – The National Institute on Deafness and Other Communication Disorders (2016), Statistics on voice, speech, and language, https://www.nidcd.nih.gov/health/statistics/statistics-voice-speech-and-language#1, July.
• 28. Niebudek-Bogusz E., Śliwińska-Kowalska M. (2006), Applicability of voice acoustic analysis with vocal loading test to diagnostics of occupational voice diseases [in Polish: Ocena przydatności analizy akustycznej z zastosowaniem próby obciążeniowej w diagnostyce chorób zawodowych narządu głosu], Medycyna Pracy, 57, 6, 497-506.
• 29. Personally Identifiable Information Protection Act [in Polish: Ustawa z dnia 10 maja 2018 r. o ochronie danych osobowych], Dz.U. 2018 poz. 1000 of May 10, 2018.
• 30. PHP The Right Way (2019), http://www.phptherightway.com, access in January 2019.
• 31. Pruszewicz A. (1992), Professional voice disorders [in Polish: Zawodowe zaburzenia głosu], [in:] Foniatria kliniczna, Państwowy Zakład Wydawnictw Lekarskich, Warszawa, pp. 205-209.
• 32. Siupsinskiene N., Lycke H. (2011), Effects of vocal training on singing and speaking voice characteristics in vocally healthy adults and children based on choral and nonchoral data, Journal of Voice, 25, 4, e177-e189, https://doi.org/10.1016/j.jvoice.2010.03.010.
• 33. Stasak B., Epps J. (2017), Differential performance of automatic speech-based depression classification across smartphones, [in:] 2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), pp. 171-175, 23-26 October, San Antonio, TX, USA, https://doi.org/10.1109/ACIIW.2017.8272609.
• 34. Szklanny K., Gubrynowicz R., Iwanicka-Pronicka K., Tylki-Szymańska A. (2016), Analysis of voice quality in patients with late-onset Pompe disease, Orphanet Journal of Rare Diseases, 11, 99, https://doi.org/10.1186/s13023-016-0480-5.
• 35. Szklanny K., Gubrynowicz R., Ratyńska J., Chojnacka-Wądołowska D. (2019), Electroglotto-graphic and acoustic analysis of voice in children with vocal nodules, International Journal of Pediatric Otorhinolaryngology, 22, 82-88, https://doi.org/10.1016/j.ijporl.2019.03.030.
• 36. Szklanny K., Gubrynowicz R., Tylki-Szymańska A. (2018), Voice alterations in patients with Morquio A syndrome, Journal of Applied Genetics, 59, 1, 73-80, https://doi.org/10.1007/s13353-017-0421-6.
• 37. Szklanny K., Tylki-Szymańska A. (2018), Follow-up analysis of voice quality in patients with late-onset Pompe disease, Orphanet Journal of Rare Diseases, 13, 189, https://doi.org/10.1186/s13023-018-0932-1.
• 38. Titze I. R., Sundberg J. (1992), Vocal intensity in speakers and singers, The Journal of the Acoustical Society of America, 91, 2936, https://doi.org/10.1121/1.402929.
• 39. Vaiano T., Guerrieri A. C., Behlau M. (2013), Body pain in classical choral singers, CoDAS, 25, 4, 303-309.
• 40. van Leer E., Pfister R. C., Zhou X. (2017), An iOS-based cepstral peak prominence application: feasibility for patient practice of resonant voice, Journal of Voice, 31, 1, 131.e9-131.e16, https://doi.org/10.1016/j.jvoice.2015.11.022.
• 41. Ventola C. L. (2014), Mobile devices and apps for health care professionals: uses and benefits, P & T: A Peer-Reviewed Journal for Formulary Management, 39, 5, 356-364.
• 42. Verde L., De Pietro G., Veltri P., Sannino G. (2015), An m-health system for the estimation of voice disorders, [in:] 2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015, 29 June-3 July, Turin, Italy, pp. 1-6, https://doi.org/10.1109/ICMEW.2015.7169766.
• 43. Voice Analyst app, Google Play, https://play.google.com/store/apps/details?id=co.speechtools.voiceanalyst&hl=pl, access in January 2019.
• 44. Voice Online Lab, Google Play, https://play.google.com/store/apps/details?id=com.voicecs.onlinelab&hl=en_US, access in January 2019.
• 45. Wilson K. (2016), The clean architecture in PHP, Lean Publishing.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).