Effect of Functional Endoscopic Sinus Surgery on Voice and Speech Recognition



      Functional Endoscopic Sinus Surgery (FESS) is the surgery of choice for nasal polyposis and chronic rhinosinusitis. The aim of our study is to assess the influence of this surgery in the acoustic parameters of voice, and their implications in the systems of identification or verification of the speaker through the speech.

      Material and methods

      A prospective study was performed between January 2017 and June 2017 including two groups of patients: those undergoing FESS, and a control group. Demographic data and GRBAS assessment were statistically analyzed. In addition, a recording of patients’ voices was made with a subsequent acoustic analysis and automatic identification of the speaker through machine learning systems, establishing the equal error rate. Samples were taken before surgery, 2 weeks after surgery and 3 months later.


      After FESS, a significant difference was observed in Grade, Roughness, Breathiness, Asthenia, Strain (GRBAS). Besides, acoustic analysis showed a significance decrease in fundamental frequency (F0), when compared with the control group. For the automatic identification of the speaker through computer systems, we found that the equal error rate is higher in the FESS group.


      Results suggest that FESS produce a decrease of F0 and changes in the vocal tract that derive in an increase in the error of recognition of the speaker in FESS patients.

      Key Words

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        • Fokkens W.J.
        • Lund V.J.
        • Mullol J.
        • et al.
        European Position Paper on Rhinosinusitis and Nasal Polyps 2012.
        Rhinol Suppl [Internet]. 2012; 23: 1-298
        • Stammberger H.
        Functional Endoscopic Sinus Surgery: The Messerklinger Technique.
        Decker, Philadelphia, EEUU1991
        • Wigand M.E.
        Transnasal ethmoidectomy under endoscopical control.
        Rhinology. 1981; 19: 7-15
        • Havel M.
        • Kornes T.
        • Weitzberg E.
        • et al.
        Eliminating paranasal sinus resonance and its effects on acoustic properties of the nasal tract.
        Logoped Phoniatr Vocol. 2016; 41: 33-40
        • Havel M.
        • Ertl L.
        • Bauer D.
        • et al.
        Resonator properties of paranasal sinuses: preliminary results of an anatomical study.
        Rhinology. 2014; 52: 178-182
        • Ungor C.
        • Saridogan C.
        • Yilmaz M.
        • et al.
        An acoustical analysis of the effects of maxillary sinus augmentation on voice quality.
        Oral Surg Oral Med Oral Pathol Oral Radiol. 2013; 115: 175-184
        • Kim Y.H.
        • Lee S.H.
        • Park C.W.
        • et al.
        Nasalance change after sinonasal surgery: analysis of voice after septoturbinoplasty and endoscopic sinus surgery.
        Am J Rhinol Allergy. 2013; 27: 67-70
        • Brandt M.G.
        • Rotenberg B.W.
        • Moore C.C.
        • et al.
        Impact of nasal surgery on speech resonance.
        Ann Otol Rhinol Laryngol. 2014; 123: 564-570
        • Acar A.
        • Cayonu M.
        • Ozman M.
        • et al.
        Changes in acoustic parameters of voice after endoscopic sinus surgery in patients with nasal polyposis.
        Indian J Otolaryngol Head Neck Surg. 2014; 66: 381-385
        • Beigi H.
        Speaker recognition: advancements and challenges.
        New Trends and Developments in Biometrics. InTech, 2012
        • Aron J.
        How innovative is Apple's new voice assistant, Siri?.
        New Sci. 2011; 212: 24-29
        • Moro-Velázquez L.
        • Gómez-García J.A.
        • Godino-Llorente J.I.
        • et al.
        Analysis of speaker recognition methodologies and the influence of kinetic changes to automatically detect Parkinson's Disease.
        Appl Soft Comput J. 2018; 62: 649-666
        • Núñez Batalla F.
        • Corte Santos P.
        • Sequeiros Santiago G.
        Evaluación Perceptual de la Disfonía: Correlación con los Parámetros Acústicos y Fiabilidad.
        Acta Otorrinolaringol Esp. 2004; 55: 282-287
        • Pereira E.R.B.NB.N.
        • Tavares E.L.M.
        • Martins R.H.G.
        Voice disorders in teachers: clinical, videolaryngoscopical, and vocal aspects.
        J Voice. 2015; 29: 564-571
        • Godino-Llorente J.I.
        • Osma-Ruiz V.
        • Sáenz-Lechón N.
        • et al.
        Acoustic analysis of voice using WPCVox: a comparative study with Multi Dimensional Voice Program.
        Eur Arch Oto-Rhino-Laryngology. 2008; 265: 465-476
        • Mehta D.D.
        • Rudoy D.
        • Wolfe P.J.
        Kalman-based autoregressive moving average modeling and inference for formant and antiformant tracking.
        J Acoust Soc Am. 2012; 13217321746
        • Rajan P.
        • Afanasyev A.
        • Hautamäki V.
        • et al.
        From single to multiple enrollment i-vectors: practical PLDA scoring variants for speaker verification.
        Digit Signal Process. 2014; 31: 93-101
        • Povey D.
        • Ghoshal A.
        • Boulianne G.
        • et al.
        The Kaldi speech recognition toolkit.
        in: IEEE 2011 workshop on automatic speech recognition and understanding. IEEE Signal Process Soc. 2011
        • Moreno A.
        • Poch D.
        • Bonafonte A.
        • et al.
        Albayzin speech database: design of the phonetic corpus.
        in: Eurospeech 1993 Proc 3rd Eur Conf Speech Commun Technol. 1. 1993: 175-178
        • Dehak N.
        • Kenny P.J.
        • Dehak R.
        • et al.
        Front-end factor analysis for speaker verification.
        IEEE Trans Audio Speech Lang Process. 2011; 19: 788-798
        • Koo S.K.
        • Kwon S.B.
        • Chon K.M.
        • et al.
        The role of the maxillary sinus on the voice.
        Eur Arch Otorhinolaryngol. 2015; 272: 2347-2350
        • Kim S.D.
        • Park H.J.
        • Kim G.H.
        • et al.
        Changes and recovery of voice quality after sinonasal surgery.
        Eur Arch Oto Rhino Laryngology. 2015; 272: 2853-2859
        • Haque S.
        • Ali M.H.
        • Haque A.K.M.F.
        Variability of acoustic features of hypernasality and it's assessment.
        Int J Adv Comput Sci Appl. 2016; 7: 195-201
        • Moro-Velázquez L.
        • Gómez-García J.A.
        • Godino-Llorente J.I.
        • et al.
        Modulation spectra morphological parameters: a new method to assess voice pathologies according to the GRABS scale.
        BioMed Res Int. 2015; : 1-13
        • Arias-Londoño J.D.
        • Godino-Llorente J.I.
        • Sáenz-Lechón N.
        • et al.
        Automatic detection of pathological voices using complexity measures, noise parameters, and mel-cepstral coefficients.
        IEEE Trans Biomed Eng. 2011; 58: 370-379