Relation of RBH Auditory-Perceptual Scale to Acoustic and Electroglottographic Voice Analysis in Children With Vocal Nodules

The aim of this paper was to present an analysis of the feasibility of voice quality prediction on the roughness, breathiness, hoarseness (RBH) scale for children with vocal nodules on the basis of both acoustic parameters and electroglottographic (EGG) examination. The first step to achieve this goal involved the creation of a dedicated database, Voice Pathology Analysis Database (VPADB), containing voice recordings from patients, the EGG signal, medical diagnosis, and the classification of voice quality on the above-mentioned scale. The database also contains data concerning the patients’ age and sex. The next step involved performing statistical analyses to test the relationship between the values of objective parameters, such as peak slope and normalized amplitude quotient, and the classification of voice quality. The study made use of voice recordings of 57 patients with vocal nodules and 37 healthy individuals. The RBH classification was carried out by two independent voice specialists. It was found that speech signal parameters can be used to predict expert evaluation with regard to roughness and hoarseness.

[1]  Joseana Macêdo Fechine,et al.  Feature Estimation for Vocal Fold Edema Detection Using Short-Term Cepstral Analysis , 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

[2]  M. Johns Update on the etiology, diagnosis, and treatment of vocal fold nodules, polyps, and cysts , 2003, Current opinion in otolaryngology & head and neck surgery.

[3]  Paavo Alku,et al.  Parabolic spectral parameter - A new method for quantification of the glottal flow , 1997, Speech Commun..

[4]  John Kane,et al.  Wavelet Maxima Dispersion for Breathy to Tense Voice Discrimination , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[5]  R. Nuss,et al.  A grading scale for pediatric vocal fold nodules , 2007, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[6]  J. Liljencrants,et al.  Dept. for Speech, Music and Hearing Quarterly Progress and Status Report a Four-parameter Model of Glottal Flow , 2022 .

[7]  R. Nuss,et al.  Validation of a Pediatric Vocal Fold Nodule Rating Scale Based on Digital Video Images , 2012, The Annals of otology, rhinology, and laryngology.

[8]  Adnane Cherif,et al.  Artificial Neural Networks and Support Vector Machine for Voice Disorders Identification , 2016 .

[9]  T. Hacki Klassifizierung von Glottisdysfunktionen mit Hilfe der Elektroglottographie , 1989 .

[10]  Hugo Fastl,et al.  Psychoacoustics: Facts and Models , 1990 .

[11]  Khalid Daoudi,et al.  On classification between normal and pathological voices using the MEEI-kayPENTAX database: issues and consequences , 2014, INTERSPEECH.

[12]  Robert Kail,et al.  Human Development: A Life-Span View , 1999 .

[13]  Ingo R. Titze,et al.  Principles of voice production , 1994 .

[14]  D G Childers,et al.  Vocal quality factors: analysis, synthesis, and perception. , 1991, The Journal of the Acoustical Society of America.

[15]  R. Martins,et al.  Perceptual and acoustic parameters of vocal nodules in children. , 2014, International journal of pediatric otorhinolaryngology.

[16]  K. D. Donohue,et al.  Effects of Vocal Fold Nodules on Glottal Cycle Measurements Derived from High-Speed Videoendoscopy in Children , 2016, PloS one.

[17]  P. Alku,et al.  Normalized amplitude quotient for parametrization of the glottal flow. , 2002, The Journal of the Acoustical Society of America.

[19]  M. Hirano,et al.  Clinical Examination of Voice , 1981 .

[20]  Mohamed Fezari,et al.  Acoustic Analysis for Detection of Voice Disorders Using Adaptive Features and Classifiers , 2014 .

[21]  J. Hillenbrand,et al.  Acoustic correlates of breathy vocal quality: dysphonic voices and continuous speech. , 1996, Journal of speech and hearing research.

[22]  Pedro Gómez Vilda,et al.  Methodological issues in the development of automatic systems for voice pathology detection , 2006, Biomed. Signal Process. Control..

[23]  Martin Rothenberg A multichannel electroglottograph , 1992 .

[24]  R. Gubrynowicz,et al.  Analysis of voice quality in patients with late-onset Pompe disease , 2016, Orphanet Journal of Rare Diseases.

[25]  Domingos Hiroshi Tsuji,et al.  GRBAS and Cape-V scales: high reliability and consensus when applied at different times. , 2012, Journal of voice : official journal of the Voice Foundation.

[26]  D. Howard Variation of electrolaryngographically derived closed quotient for trained and untrained adult female singers. , 1995, Journal of voice : official journal of the Voice Foundation.

[27]  A. Tylki-Szymańska,et al.  Follow-up analysis of voice quality in patients with late-onset Pompe disease , 2018, Orphanet Journal of Rare Diseases.

[28]  R. Hillman,et al.  Consensus auditory-perceptual evaluation of voice: development of a standardized clinical protocol. , 2009, American journal of speech-language pathology.

[29]  John Kane,et al.  Identifying Regions of Non-Modal Phonation Using Features of the Wavelet Transform , 2011, INTERSPEECH.

[30]  Meisam Khalil Arjmandi,et al.  An efficient voice pathology classification scheme based on applying multi-layer linear discriminant analysis to wavelet packet-based features , 2014, Biomed. Signal Process. Control..

[31]  I R Titze,et al.  Vocal intensity in speakers and singers. , 1991, The Journal of the Acoustical Society of America.

[32]  N. Isshiki,et al.  Differential diagnosis of hoarseness. , 1969, Folia phoniatrica.

[33]  E Fresnel-Elbaz,et al.  Differentiated perceptual evaluation of pathological voice quality: reliability and correlations with acoustic measurements. , 1996, Revue de laryngologie - otologie - rhinologie.

[34]  G. Dursun,et al.  Changes after voice therapy in objective and subjective voice measurements of pediatric patients with vocal nodules , 2009, European Archives of Oto-Rhino-Laryngology.

[35]  F. Liang,et al.  Correlation among the dysphonia severity index (DSI), the RBH voice perceptual evaluation, and minimum glottal area in female patients with vocal fold nodules. , 2014, Journal of voice : official journal of the Voice Foundation.

[36]  I. Deary,et al.  Measuring voice outcomes: state of the science review , 2009, The Journal of Laryngology & Otology.

[37]  R. Gubrynowicz,et al.  Voice alterations in patients with Morquio A syndrome , 2017, Journal of Applied Genetics.

[38]  John Kane,et al.  COVAREP — A collaborative voice analysis repository for speech technologies , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[39]  G. de Krom,et al.  Consistency and reliability of voice quality ratings for different types of speech fragments. , 1994, Journal of speech and hearing research.

[40]  A. Ysunza,et al.  Voice parameters and videonasolaryngoscopy in children with vocal nodules: a longitudinal study, before and after voice therapy. , 2012, International journal of pediatric otorhinolaryngology.

[41]  G. Fant Dept. for Speech, Music and Hearing Quarterly Progress and Status Report the Lf-model Revisited. Transformations and Frequency Domain Analysis the Lf-model Revisited. Transformations and Frequency Domain Analysis* , 2022 .

[42]  Hariharan Muthusamy,et al.  Optimal Selection of Long Time Acoustic Features Using GA for the Assessment of Vocal Fold Disorders , 2012 .

[43]  P. Dejonckere,et al.  A basic protocol for functional assessment of voice pathology, especially for investigating the efficacy of (phonosurgical) treatments and evaluating new assessment techniques , 2001, European Archives of Oto-Rhino-Laryngology.

[44]  B. Barsties,et al.  Assessment of voice quality: Current state-of-the-art. , 2015, Auris, nasus, larynx.

[45]  Babak Seyed Aghazadeh,et al.  Optimal feature selection for the assessment of vocal fold disorders , 2009, Comput. Biol. Medicine.

[46]  E. Pelland-Blais,et al.  Computer-assisted voice analysis: establishing a pediatric database. , 2002, Archives of otolaryngology--head & neck surgery.

[47]  R. Nuss,et al.  Correlation of Vocal Fold Nodule Size in Children and Perceptual Assessment of Voice Quality , 2010, The Annals of otology, rhinology, and laryngology.

[48]  G. Lindsey,et al.  Toward the Quantification of Vocal Efficiency , 1990 .

[49]  Ghulam Muhammad,et al.  Automatic voice pathology detection and classification using vocal tract area irregularity , 2016 .

[50]  E Abberton,et al.  First applications of a new laryngograph. , 1971, Medical & biological illustration.