Advertisement

A Study on Voice Measures in Patients With Alzheimer's Disease

  • Noé Xiu
    Affiliations
    U.R. 1339 Linguistique, Langues et Parole (LiLPa) and Institut de Phonétique de Strasbourg (IPS) - Université de Strasbourg, France

    Memory Clinic and Neurology Inpatient Department, Zigong First People's Hospital, China

    Interdisciplinary Research Center for Linguistic Science, University of Science and Technology of China, China
    Search for articles by this author
  • Béatrice Vaxelaire
    Affiliations
    U.R. 1339 Linguistique, Langues et Parole (LiLPa) and Institut de Phonétique de Strasbourg (IPS) - Université de Strasbourg, France
    Search for articles by this author
  • Lanlan Li
    Affiliations
    Interdisciplinary Research Center for Linguistic Science, University of Science and Technology of China, China
    Search for articles by this author
  • Zhenhua Ling
    Affiliations
    Interdisciplinary Research Center for Linguistic Science, University of Science and Technology of China, China

    National Engineering Research Center of Speech and Language Information Processing, University of Science and Technology of China, China
    Search for articles by this author
  • Xiaoya Xu
    Affiliations
    Memory Clinic and Neurology Inpatient Department, Zigong First People's Hospital, China
    Search for articles by this author
  • Linming Huang
    Affiliations
    Memory Clinic and Neurology Inpatient Department, Zigong First People's Hospital, China
    Search for articles by this author
  • Bo Sun
    Correspondence
    Address correspondence and reprint requests to Bo Sun, University of Science and Technology of China, No.96, JinZhai Road Baohe District, Hefei, P.R. China.
    Affiliations
    Interdisciplinary Research Center for Linguistic Science, University of Science and Technology of China, China
    Search for articles by this author
  • Lin Huang
    Correspondence
    Address correspondence and reprint requests to Lin Huang, Memory Clinic and Neurology Inpatient Department, Zigong First People's Hospital, No. 42, Shangyihao Yizhi Road Ziliujing District, Zigong, P.R. China.
    Affiliations
    Memory Clinic and Neurology Inpatient Department, Zigong First People's Hospital, China
    Search for articles by this author
  • Rudolph Sock
    Affiliations
    U.R. 1339 Linguistique, Langues et Parole (LiLPa) and Institut de Phonétique de Strasbourg (IPS) - Université de Strasbourg, France

    Language, Information and Communication Laboratory – LICOLAB, Pavol Jozef Šafárik University, Košice, Slovakia
    Search for articles by this author
Published:September 21, 2022DOI:https://doi.org/10.1016/j.jvoice.2022.08.010

      Summary

      Objective

      As Alzheimer's disease (AD) might provoke certain nerve disorders, patients with AD can acquire sensorimotor adaptation problems, and thus the acoustic characteristics of the speech they produce may differ from those of healthy subjects. This study aimed to (1) extract acoustic characteristics (relating to articulatory gestures) potentially useful for detecting AD and (2) examine whether these characteristics could help identify AD patients.

      Methods

      A total of 50 individuals participated in the study, including the AD group (17 cases), the Neurologically Healthy (NH) group (13 cases), the Mild Cognitive Impairment (MCI) group (11 cases), and the Vascular Cognitive Impairment (VCI) group (9 cases). Voice samples involving three vowels (/i/, /a/, and /u/) and six consonants (/p/, /pʰ/, /t/, /tʰ/, /k/, and /kʰ/) were collected using a digital recorder (TASCAM DR40X). Microphone-to-mouth distance was maintained at 30 cm. Acoustic measures included F0, jitter, shimmer, HNR, F1, F2, F3, and VOT.

      Results

      One-way ANOVA tests were carried out to compare the acoustic measures among the four groups. F3 of vowel /u/, F2 bandwidth of vowel /a/, VOT of consonant /t/, and male participants’ F0 of three vowels (/a/, /i/, and /u/) were found significantly different, while no significant differences were found in the other measures.

      Conclusion

      Some acoustic characteristics can indeed help detect AD patients.

      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

        • Sabayan B
        • Sorond F.
        Reducing risk of dementia in older age.
        JAMA. 2017; 317: 2028
        • Haines JL.
        Alzheimer disease: perspectives from epidemiology and genetics.
        J Law Med Ethics. 2018; 46: 694-698
        • Takizawa C
        • Thompson PL
        • van Walsem A
        • et al.
        Epidemiological and economic burden of Alzheimer's disease: a systematic literature review of data across Europe and the United States of America.
        J Alzheimers Dis. 2015; 43: 1271-1284
        • Tahami Monfared AA
        • Byrnes MJ
        • White LA
        • et al.
        The Humanistic and economic burden of alzheimer's disease.
        Neurol Therapy. 2022; : 1-27
        • Niemantsverdriet E
        • Valckx S
        • Bjerke M
        • et al.
        Alzheimer's disease CSF biomarkers: clinical indications and rational use.
        Acta Neurol Belg. 2017; 117: 591-602
        • Sahrim M.
        Blood Vessel Shape Description for Detection of Alzheimer's Disease.
        University of Southampton, 2016
        • Yancheva M
        • Fraser KC
        • Rudzicz F.
        Using linguistic features longitudinally to predict clinical scores for Alzheimer's disease and related dementias.
        in: Proceedings of SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies. 2015: 134-139
        • Wang X
        • Li F
        • Gao Q
        • et al.
        Evaluation of the accuracy of cognitive screening tests in detecting dementia associated with Alzheimer's disease: A hierarchical Bayesian latent class meta-analysis.
        J Alzheimers Dis. 2022; : 1-20
        • Gavrilova SI
        • Alvarez A.
        Cerebrolysin in the therapy of mild cognitive impairment and dementia due to Alzheimer's disease: 30 years of clinical use.
        Med Res Rev. 2021; 41: 2775-2803
        • Fang R
        • Wang G
        • Huang Y
        • et al.
        Validation of the Chinese version of Addenbrooke's cognitive examination-revised for screening mild Alzheimer's disease and mild cognitive impairment.
        Dement Geriatr Cogn Disord. 2014; 37: 223-231
        • Hoops S
        • Nazem S
        • Siderowf A
        • et al.
        Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease.
        Neurology. 2009; 73: 1738-1745
        • Matias-Guiu JA
        • Valles-Salgado M
        • Rognoni T
        • et al.
        Comparative diagnostic accuracy of the ACE-III, MIS, MMSE, MoCA, and RUDAS for screening of Alzheimer disease.
        Dement Geriatr Cogn Disord. 2017; 43: 237-246
        • Hoffmann I
        • Nemeth D
        • Dye CD
        • et al.
        Temporal parameters of spontaneous speech in Alzheimer's disease.
        Int J Speech-Langu Patho. 2010; 12: 29-34
        • Winblad B
        • Amouyel P
        • Andrieu S
        • et al.
        Defeating Alzheimer's disease and other dementias: a priority for European science and society.
        Lancet Neurol. 2016; 15: 455-532
        • Morris JC
        • Storandt M
        • Miller JP
        • et al.
        Mild cognitive impairment represents early-stage Alzheimer disease.
        Arch Neurol. 2001; 58: 397-405
        • Shen D
        • Wee C-Y
        • Zhang D
        • et al.
        Machine learning techniques for AD/MCI diagnosis and prognosis.
        Machine Learning in Healthcare Informatics. Springer, 2014: 147-179
        • Dichgans M
        • Leys D.
        Vascular cognitive impairment.
        Circ Res. 2017; 120: 573-591
        • Hou Y
        • Dan X
        • Babbar M
        • et al.
        Ageing as a risk factor for neurodegenerative disease.
        Nat Rev Neurol. 2019; 15: 565-581
        • Calne DB
        • Eisen A.
        The relationship between Alzheimer's disease, Parkinson's disease and motor neuron disease.
        Can J Neurol Sci. 1989; 16: 547-550
        • McRae PA
        • Tjaden K
        • Schoonings B.
        Acoustic and perceptual consequences of articulatory rate change in Parkinson disease.
        J Speech Lang Hear R. 2002; 45: 35-50
        • Hoehn MM
        • Yahr MD.
        Parkinsonism: onset, progression and mortality.
        Neurology. 1967; 17: 427-442
        • Bang YI
        • Min K
        • Sohn YH
        • et al.
        Acoustic characteristics of vowel sounds in patients with Parkinson disease.
        NeuroRehabilitation. 2013; 32: 649-654
        • Dromey C
        • Ramig LO
        • Johnson AB.
        Phonatory and articulatory changes associated with increased vocal intensity in Parkinson disease: a case study.
        J Speech Hear Res. 1995; 38: 751-764
      1. Warnita T, Inoue N, Shinoda K. Detecting Alzheimer's disease using gated convolutional neural network from audio data. arXiv preprint arXiv:1803.11344. 2018.

        • Eyben F
        • Weninger F
        • Gross F
        • et al.
        Recent developments in opensmile, the munich open-source multimedia feature extractor.
        in: Proceedings of the 21st ACM international conference on Multimedia. 2013: 835-838
        • Schuller B
        • Steidl S
        • Batliner A.
        The interspeech 2009 emotion challenge.
        in: Proceedings of Interspeech. 2009: 312-315
        • Swords GM
        • Nguyen LT
        • Mudar RA
        • et al.
        Auditory system dysfunction in Alzheimer disease and its prodromal states: A review.
        Ageing Res Rev. 2018; 44: 49-59
        • Amir O
        • Wolf M
        • Amir N.
        A clinical comparison between two acoustic analysis softwares: MDVP and Praat.
        Biomed Signal Process Control. 2009; 4: 202-205
        • Kanjee R
        • Watter S
        • Sévigny A
        • et al.
        A case of foreign accent syndrome: Acoustic analyses and an empirical test of accent perception.
        J Neurolinguistics. 2010; 23: 580-598
        • Goberman AM
        • Elmer LW.
        Acoustic analysis of clear versus conversational speech in individuals with Parkinson disease.
        J Commun Disord. 2005; 38: 215-230
        • Teixeira JP
        • Oliveira C
        • Lopes C.
        Vocal acoustic analysis–jitter, shimmer and hnr parameters.
        Procedia Technol. 2013; 9: 1112-1122
        • Dankbaar JW
        • Pameijer FA.
        Vocal cord paralysis: anatomy, imaging and pathology.
        Insights into Imaging. 2014; 5: 743-751
        • Joos M
        Acoustic phonetics.
        Language. 1948; 24: 5-136
        • Xiu N.
        Perturbation de la production de la parole chez le patient atteint d'une paralysie laryngée: données acoustiques et aérodynamiques.
        Université de Strasbourg, 2018
        • Abramson AS
        • Whalen DH.
        Voice Onset Time (VOT) at 50: Theoretical and practical issues in measuring voicing distinctions.
        J Phonetics. 2017; 63: 75-86
        • Lisker L
        • Abramson AS.
        A cross-language study of voicing in initial stops: Acoustical measurements.
        Word. 1964; 20: 384-422
        • Klatt DH.
        Voice onset time, frication, and aspiration in word-initial consonant clusters.
        J Speech Hear Res. 1975; 18: 686-706
        • Baker J
        • Ryalls J
        • Brice A
        • et al.
        Voice onset time production in speakers with Alzheimer's disease.
        Clin Linguist Phonet. 2007; 21: 859-867
        • Kumar SP
        • Svec JG.
        A Simple Method to Obtain Basic Acoustic Measures From Video Recordings as Subtitles.
        J Speech Lang Hear R. 2018; 61: 2196-2204
        • Arevalo-Rodriguez I
        • Smailagic N
        • i Figuls MR
        • et al.
        Mini-Mental State Examination (MMSE) for the detection of Alzheimer's disease and other dementias in people with mild cognitive impairment (MCI).
        Cochrane Database Systemat Rev. 2015;
        • Costa AS
        • Reich A
        • Fimm B
        • et al.
        Evidence of the sensitivity of the MoCA alternate forms in monitoring cognitive change in early Alzheimer's disease.
        Dement Geriatr Cogn Disord. 2014; 37: 95-103
        • Petersen RC.
        Mild cognitive impairment as a diagnostic entity.
        J Intern Med. 2004; 256: 183-194
        • McKhann GM
        • Knopman DS
        • Chertkow H
        • et al.
        The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease.
        Alzheimer's & Dementia. 2011; 7: 263-269
        • Gorelick PB
        • Scuteri A
        • Black SE
        • et al.
        Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association.
        Stroke. 2011; 42: 2672-2713
        • Dejonckere P
        • Crevier-Buchman L
        • Marie J
        • et al.
        Implementation of the European Laryngological Society (ELS) basic protocol for assessing voice treatment effect.
        Revue de laryngologie-otologie-rhinologie. 2003; 124: 279-283
        • Skelton RB.
        Individuality in the vowel triangle.
        Phonetica. 1970; 21: 129-137
      2. Nasreen S, Hough J, Purver M. Detecting Alzheimer's Disease using Interactional and Acoustic features from Spontaneous Speech: Interspeech; 2021.

        • Hanson HM
        • Chuang ES.
        Glottal characteristics of male speakers: Acoustic correlates and comparison with female data.
        J Acoust Soc Am. 1999; 106: 1064-1077