Research Article| Volume 37, ISSUE 2, P300.e11-300.e20, March 2023

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Towards the Objective Speech Assessment of Smoking Status based on Voice Features: A Review of the Literature

Published:January 22, 2021DOI:


      Background and Objective

      In smoking cessation clinical research and practice, objective validation of self-reported smoking status is crucial for ensuring the reliability of the primary outcome, that is, smoking abstinence. Speech signals convey important information about a speaker, such as age, gender, body size, emotional state, and health state. We investigated (1) if smoking could measurably alter voice features, (2) if smoking cessation could lead to changes in voice, and therefore (3) if the voice-based smoking status assessment has the potential to be used as an objective smoking cessation validation method.


      A systematic review of the scientific literature was conducted to compile studies on smoking status assessment based on voice features. We searched nine scientific databases for original studies involving the effects of smoking on voice features, the effects of smoking cessation on voice features.


      A total of 34 studies were identified for review. We found that fundamental frequency, jitter, shimmer, harmonics to noise ratio, and other voice features are affected by smoking and could be used to assess smoking status.


      Speech assessment of smoking status based on voice features has potential as a smoking status validation method, as it is simple, reliable, and less time-consuming. Furthermore, this study provides recommendations for future research on the objective speech assessment of smoking status based on voice features.


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        • Forouzanfar MH
        • Afshin A
        • Alexander LT
        • et al.
        Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015.
        Lancet. 2016; 388: 1659-1724
        • Piper ME
        • Bullen C
        • Krishnan-Sarin S
        • et al.
        Defining and measuring abstinence in clinical trials of smoking cessation interventions: an updated review.
        Nicotine Tob Res. 2019; (Published online)
        • West Hajek P
        • Stead L
        • Stapleton J
        Outcome criteria in smoking cessation trials: proposal for a common standard.
        Addiction. 2005; 100: 299-303
        • Cheung KL
        • De Ruijter D
        • Hiligsmann M
        • et al.
        Exploring consensus on how to measure smoking cessation. A Delphi study.
        BMC Public Health. 2017; 17
        • Wiskirska-Woźnica B
        • Wojnowski W
        The smokers voice self assessment based on Voice Handicap Index (VHI).
        Przegla̧d Lek. 2009; 66: 565-566
        • Tafiadis D
        • Chronopoulos SK
        • Kosma EI
        • et al.
        Using receiver operating characteristic curve to define the cutoff points of voice handicap index applied to young adult male smokers.
        J Voice. 2018; 32: 443-448
        • Shaffer HJ
        • Eber GB
        • Hall MN
        • et al.
        Smoking behavior among casino employees: self-report validation using plasma cotinine.
        Addict Behav. 2000; 25: 693-704
        • Benowitz NL
        • Bernert JT
        • Foulds J
        • et al.
        Biochemical verification of tobacco use and abstinence: 2019 update.
        Nicotine Tob Res. 2019; (Published online)
        • Scheuermann TS
        • Richter KP
        • Rigotti NA
        • et al.
        Accuracy of self-reported smoking abstinence in clinical trials of hospital-initiated smoking interventions.
        Addiction. 2017; 112: 2227-2236
        • Reid JL
        • Hammond D
        • Boudreau C
        • et al.
        Socioeconomic disparities in quit intentions, quit attempts, and smoking abstinence among smokers in four western countries: findings from the International Tobacco Control Four Country Survey.
        Nicotine Tob Res. 2010; 12
        • Houston TK
        • Scarinci IC
        • Person SD
        • et al.
        Patient smoking cessation advice by health care providers: the role of ethnicity, socioeconomic status, and health.
        Am J Public Health. 2005; 95: 1056-1061
        • Singh R
        • Keshet J
        • Gencaga D
        • et al.
        The relationship of voice onset time and voice offset time to physical age.
        ICASSP, IEEE Int Conf Acoust Speech Signal Process - Proceedings. 2016; May: 5390-5394
        • Doukhan D
        • Carrive J
        • Vallet F
        • et al.
        An open-source speaker gender detection framework for monitoring gender equality.
        ICASSP, IEEE Int Conf Acoust Speech Signal Process - Proceedings. 2018; April: 5214-5218
        • Mporas I
        • Ganchev T
        Estimation of unknown speaker's height from speech.
        Int J Speech Technol. 2009; 12: 149-160
        • Swain M
        • Routray A
        • Kabisatpathy P
        Databases, features and classifiers for speech emotion recognition: a review.
        Int J Speech Technol. 2018; 21: 93-120
        • Poorjam AH
        • Little MA
        • Jensen JR
        • et al.
        A parametric approach for classification of distortions in pathological voices.
        ICASSP, IEEE Int Conf Acoust Speech Signal Process - Proceedings. 2018; April: 286-290
        • CDC
        How Tobacco Smoke Causes Disease The Biology and Behavioral Basis for Smoking-Attributable Disease. A Report of the Surgeon General.
        Public Health. 2010; (Published online. Available at)
        • Marcotullio D
        • Magliulo G
        • Pezone T
        Reinke's edema and risk factors: clinical and histopathologic aspects.
        Am J Otolaryngol - Head Neck Med Surg. 2002; 23: 81-84
        • Yanbaeva DG
        • Dentener MA
        • Creutzberg EC
        • et al.
        Systemic effects of smoking.
        Chest. 2007; 131: 1557-1566
        • Gonzalez J
        • Carpi A
        Early effects of smoking on the voice: a multidimensional study.
        Med Sci Monit. 2004; 10
        • Guimarães I
        • Abberton E
        Health and voice quality in smokers: an exploratory investigation.
        Logop Phoniatr Vocol. 2005; 30: 185-191
        • Murphy CH
        • Doyle PC
        The effects of cigarette smoking on voice-fundamental frequency.
        Otolaryngol Neck Surg. 1987; 97: 376-380
        • Awan SN
        • Morrow DL
        Videostroboscopic characteristics of young adult female smokers vs. nonsmokers.
        J Voice. 2007; 21: 211-223
        • Pinar D
        • Cincik H
        • Erkul E
        • et al.
        Investigating the effects of smoking on young adult male voice by using multidimensional methods.
        J Voice. 2016; 30: 721-725
        • Hegde S
        • Shetty S
        • Rai S
        • et al.
        A survey on machine learning approaches for automatic detection of voice disorders.
        J Voice. 2019; 33: 947.e11-947.e33
        • Wroge TJ
        • Özkanca Y
        • Demiroglu C
        • et al.
        Parkinson’s disease diagnosis using machine learning and voice.
        2018 IEEE Signal Process Med Biol Symp SPMB 2018 - Proceedings. 2019; (Published online)
        • Kim J
        • Kim J
        • Lee S
        • et al.
        Vowel based voice activity detection with LSTM recurrent neural network.
        ACM Int Conf Proceeding Ser. 2016; (Published online): 134-137
        • Elton RJ
        • Vasuki P
        • Mohanalin J
        Voice activity detection using fuzzy entropy and support vector machine.
        Entropy. 2016; 18
        • Hemmerling D
        • Skalski A
        • Gajda J
        Voice data mining for laryngeal pathology assessment.
        Comput Biol Med. 2016; 69: 270-276
        • Uloza V
        • Verikas A
        • Bacauskiene M
        • et al.
        Categorizing normal and pathological voices: automated and perceptual categorization.
        J Voice. 2011; 25: 700-708
        • Erfanian Saeedi N
        • Almasganj F
        • Torabinejad F
        Support vector wavelet adaptation for pathological voice assessment.
        Comput Biol Med. 2011; 41: 822-828
        • Sasou A
        Voice-pathology analysis based on AR-HMM.
        2016 Asia-Pacific Signal Inf Process Assoc Annu Summit Conf APSIPA 2016. 2017; (Published online)
        • Lee T
        • Liu Y
        • Yeung YT
        • et al.
        Predicting severity of voice disorder from DNN-HMM acoustic posteriors.
        Proc Annu Conf Int Speech Commun Assoc INTERSPEECH. 2016; 08-12-Sept: 97-101
        • Amara F
        • Fezari M
        • Bourouba H
        An improved GMM-SVM system based on distance metric for voice pathology detection.
        Appl Math Inf Sci. 2016; 10: 1061-1070
        • Makowski R
        • Hossa R
        Voice activity detection with quasi-quadrature filters and GMM decomposition for speech and noise.
        Appl Acoust. 2020; : 166
        • Chen HL
        • Wang G
        • Ma C
        • et al.
        An efficient hybrid kernel extreme learning machine approach for early diagnosis of Parkinson's disease.
        Neurocomputing. 2016; 184: 131-144
        • Asmae O
        • Abdelhadi R
        • Bouchaib C
        • et al.
        Parkinson's disease identification using KNN and ANN Algorithms based on Voice Disorder.
        2020 1st Int Conf Innov Res Appl Sci Eng Technol IRASET 2020. 2020; (Published online)
        • Forero M.LA
        • Kohler M
        • Vellasco MMBR
        • et al.
        Analysis and classification of voice pathologies using glottal signal parameters.
        J Voice. 2016; 30: 549-556
        • Francis CR
        • Nair VV
        • Radhika S
        A scale invariant technique for detection of voice disorders using Modified Mellin Transform.
        Proc IEEE Int Conf Emerg Technol Trends Comput Commun Electr Eng ICETT 2016. 2017; (Published online)
        • Amami R
        • Smiti A
        An incremental method combining density clustering and support vector machines for voice pathology detection.
        Comput Electr Eng. 2017; 57: 257-265
        • Schuller B
        • Rigol G
        • Lang M
        Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine - belief network architecture.
        ICASSP, IEEE Int Conf Acoust Speech Signal Process - Proceedings. 2004; : 1
        • Ueng SK
        • Luo CM
        • Tsai TY
        • et al.
        Human voice quality measurement in noisy environments.
        Technol Heal Care. 2015; 24: S313-S324
        • Talkin D
        • Kleijn WB
        • Paliwal KK
        A Robust Algorithm for Pitch Tracking (RAPT).
        Speech Coding Synth Eds Amsterdam, NetherlandsElsevier. 1995; (Published online): 495-518
        • Camacho A
        • Harris JG
        A sawtooth waveform inspired pitch estimator for speech and music.
        J Acoust Soc Am. 2008; 124: 1638-1652
        • de Cheveigné A
        • Kawahara H
        YIN, a fundamental frequency estimator for speech and music.
        J Acoust Soc Am. 2002; 111: 1917-1930
        • Mauch M
        • Dixon S.
        PYIN: A fundamental frequency estimator using probabilistic threshold distributions.
        ICASSP, IEEE Int Conf Acoust Speech Signal Process - Proceedings. 2014; (Published online): 659-663
        • Fernández Liesa R
        • Damborenea Tajada D
        • Rueda Gormedino P
        • et al.
        Acoustic analysis of the normal voice in nonsmoking adults.
        Acta Otorrinolaringol Esp. 1999; 50 (Available at): 134-141
        Date accessed: January 20, 2021
        • Jiangping K
        A study on jitter, shimmer and F0 of Mandarin infant voice by developing an applied method of voice signal processing.
        Proceedings - 1st Int Congr Image Signal Process CISP 2008. 2008; 5: 314-318
        • Rakesh K
        • Dutta S
        • Shama K
        Gender Recognition Using Speech Processing Techniques in Labview.
        Int J Adv Eng Technol. 2011; 51: 51-63
        • Horii Sorenson
        Cigarette smoking and voice fundamental frequency.
        J Commun Disord. 1982; 15: 135-144
        • Lee L
        • Stemple JC
        • Geiger D
        • et al.
        Effects of environmental tobacco smoke on objective measures of voice production.
        Laryngoscope. 1999; 109: 1531-1534
        • Farrús M
        • Hernando J
        • Ejarque P
        Jitter and shimmer measurements for speaker recognition.
        Proc Annu Conf Int Speech Commun Assoc INTERSPEECH. 2007; 2: 1153-1156
        • Awan SN
        The effect of smoking on the dysphonia severity index in females.
        Folia Phoniatr Logop. 2011; 63: 65-71
        • Chai L
        • Sprecher AJ
        • Zhang Y
        • et al.
        Perturbation and nonlinear dynamic analysis of adult male smokers.
        J Voice. 2011; 25: 342-347
        • Vincent I
        • Gilbert HR
        The effects of cigarette smoking on the female voice.
        Logop Phoniatr Vocology. 2012; 37: 22-32
        • Zealouk O
        • Satori H
        • Hamidi M
        • et al.
        Vocal parameters analysis of smoker using Amazigh language.
        Int J Speech Technol. 2018; 21: 85-91
        • Tuhanioğlu B
        • Erkan SO
        • Özdaş T
        • et al.
        The Effect of Electronic Cigarettes on Voice Quality.
        J Voice. 2019; 33: 811.e13-811.e17
        • Yumot E
        • Gould WJ
        Harmonics-to-noise ratio as an index of the degree of hoarseness.
        J Acoust Soc Am. 1982; 71: 1544-1550
        • Boersma P
        Accurate short-term analysis of the fundamental frequency and the harmonics-to-noise ratio of a sampled sound.
        Proc Inst Phonetic Sci. 1993; 17: 97-110
        • Ferrand CT
        Harmonics-to-noise ratio: An index of vocal aging.
        J Voice. 2002; 16: 480-487
        • Braun A
        The effect of cigarette smoking on vocal parameters.
        ESCA Work Autom Speak Recognition, Identification, Verif ASRIV 1994. 2019; (Published online): 161-164
        • Díaz José
        • Antonio A.Antonio
        • Arroyo HBR
        Study and proposal of parameters for the objective assessment of voice quality in smokers.
        Rev Ing UC. 2014; 21: 7-16
        • Tafiadis D
        • Toki EI
        • Miller KJ
        • et al.
        Effects of Early Smoking habits on young dult female Voices in Greece.
        J Voice. 2017; 31: 728-732
        • Gomes Lustosa Pintoa Aline
        • Agrício Nubiato Crespob LFM
        Influence of smoking isolated and associated to multifactorial aspects in vocal acoustic parameters.
        Braz J Otorhinolaryngol. 2014; 80: 60-67
        • Coleman RO
        Male and female voice quality and its relationship to vowel formant frequencies.
        J Speech Hear Res. 1971; 14: 565-577
        • Gerhard D
        Pitch Extraction and Fundamental Frequency : History and Current Techniques Theory of Pitch.
        Department of Computer Science, University of Regina Regina, Canada2003
        • Zhang Y
        • Jiang JJ
        • Wallace SM
        • et al.
        Comparison of nonlinear dynamic methods and perturbation methods for voice analysis.
        J Acoust Soc Am. 2005; 118: 2551-2560
        • Berg M
        • Fuchs M
        • Wirkner K
        • et al.
        The speaking voice in the general population: normative data and associations to sociodemographic and lifestyle factors.
        J Voice. 2017; 31: 257.e13-257.e24
        • Dirk L
        • Braun A
        Voice parameter changes in smokers during abstinence from cigarette smoking.
        Proc 17th Int Congr Phonetic Sci (ICPhS 2011). 2011; : 1-3
        • Martins RHG
        • Tavares ELM
        • Pessin ABB
        Are Vocal Alterations Caused by Smoking in Reinke's Edema in Women Entirely Reversible After Microsurgery and Smoking Cessation?.
        J Voice. 2017; 31: 380.e11-380.e14
        • Ayoub MR
        • Larrouy-Maestri P
        • Morsomme D
        The effect of smoking on the fundamental frequency of the speaking voice.
        J Voice. 2019; 33: 802.e11-802.e16
        • Hamdan AL
        • Sibai A
        • Oubari D
        • et al.
        Laryngeal findings and acoustic changes in hubble-bubble smokers.
        Eur Arch Oto-Rhino-Laryngology. 2010; 267: 1587-1592