Influence de l’attaque sur l’analyse perceptive des dysphonies

Révis, Joana; Triglia, Jean‐Michel

doi:10.1159/000048593

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…This result can be explained by the difficulty to initiate the vocal cord vibration correctly, encountered by dysphonic speakers. It confirmed the phenomenon observed manually on the attack of sustained vowels by [48], which showed the importance of the vowel onset to identify the dysphonia severity perceptually. Of course, this study needs to be pursued by observing other kinds of data.…”

Section: From Automatic Classification To Expertise: Preliminarysupporting

confidence: 83%

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

Fredouille

Pouchoulin

Ghio

et al. 2009

EURASIP J. Adv. Signal Process.

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This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists). The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices), rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0-3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

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Section: From Automatic Classification To Expertise: Preliminarysupporting

confidence: 83%

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

Fredouille

Pouchoulin

Ghio

et al. 2009

EURASIP J. Adv. Signal Process.

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“…In general, hoarseness is more present and perceptible in long vowels, especially in open vowels, vowels in voiced context, vowels after glottal closure, or in strained vowels [10]. Hence, perceptual evaluation of a vowel and speech can only be adequately compared when the entire vowel with onset is evaluated [11, 12]. For automatic evaluation, some researchers recommend examining only the stable part of an isolated vowel [13], but following these recommendations means that a substantial portion of persons whose phonation is highly irregular cannot be evaluated at all.…”

Section: Introductionmentioning

confidence: 99%

Automatic Evaluation of Voice Quality Using Text-Based Laryngograph Measurements and Prosodic Analysis

Haderlein

Schwemmle

Döllinger

et al. 2015

Computational and Mathematical Methods in Medicine

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Due to low intra- and interrater reliability, perceptual voice evaluation should be supported by objective, automatic methods. In this study, text-based, computer-aided prosodic analysis and measurements of connected speech were combined in order to model perceptual evaluation of the German Roughness-Breathiness-Hoarseness (RBH) scheme. 58 connected speech samples (43 women and 15 men; 48.7 ± 17.8 years) containing the German version of the text “The North Wind and the Sun” were evaluated perceptually by 19 speech and voice therapy students according to the RBH scale. For the human-machine correlation, Support Vector Regression with measurements of the vocal fold cycle irregularities (CFx) and the closed phases of vocal fold vibration (CQx) of the Laryngograph and 33 features from a prosodic analysis module were used to model the listeners' ratings. The best human-machine results for roughness were obtained from a combination of six prosodic features and CFx (r = 0.71, ρ = 0.57). These correlations were approximately the same as the interrater agreement among human raters (r = 0.65, ρ = 0.61). CQx was one of the substantial features of the hoarseness model. For hoarseness and breathiness, the human-machine agreement was substantially lower. Nevertheless, the automatic analysis method can serve as the basis for a meaningful objective support for perceptual analysis.

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“…Innerhalb der Methode bedeuten: G = overall grade or degree of deviance from normal (Gesamtgrad der Störung); R = rough (Rauhigkeit), B = breathy (Behauchtheit), A = asthenic (Schwächung), S = strained quality (Anspannung). Die Beschreibungsmethode findet auch in neueren europäischen Studien Verwendung [2,3,14].…”

Section: Introductionunclassified

Methodische Aspekte der auditiven Beurteilung von Stimmqualität

Pützer¹,

Barry²

2004

Sprache Stimme Gehör

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Influence de l’attaque sur l’analyse perceptive des dysphonies

Cited by 8 publications

References 14 publications

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

Automatic Evaluation of Voice Quality Using Text-Based Laryngograph Measurements and Prosodic Analysis

Methodische Aspekte der auditiven Beurteilung von Stimmqualität

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