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Autor(en): Barsties von Latoszek, Ben
Mayer, Jörg
Watts, Christopher R.
Lehnert, Bernhard
Titel: Advances in clinical voice quality analysis with VOXplot
Erscheinungsdatum: 2023
Dokumentart: Zeitschriftenartikel
Seiten: 10
Erschienen in: Journal of clinical medicine 12 (2023), No. 4644
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-136941
http://elib.uni-stuttgart.de/handle/11682/13694
http://dx.doi.org/10.18419/opus-13675
ISSN: 2077-0383
Zusammenfassung: Background: The assessment of voice quality can be evaluated perceptually with standard clinical practice, also including acoustic evaluation of digital voice recordings to validate and further interpret perceptual judgments. The goal of the present study was to determine the strongest acoustic voice quality parameters for perceived hoarseness and breathiness when analyzing the sustained vowel [a:] using a new clinical acoustic tool, the VOXplot software. Methods: A total of 218 voice samples of individuals with and without voice disorders were applied to perceptual and acoustic analyses. Overall, 13 single acoustic parameters were included to determine validity aspects in relation to perceptions of hoarseness and breathiness. Results: Four single acoustic measures could be clearly associated with perceptions of hoarseness or breathiness. For hoarseness, the harmonics-to-noise ratio (HNR) and pitch perturbation quotient with a smoothing factor of five periods (PPQ5), and, for breathiness, the smoothed cepstral peak prominence (CPPS) and the glottal-to-noise excitation ratio (GNE) were shown to be highly valid, with a significant difference being demonstrated for each of the other perceptual voice quality aspects. Conclusions: Two acoustic measures, the HNR and the PPQ5, were both strongly associated with perceptions of hoarseness and were able to discriminate hoarseness from breathiness with good confidence. Two other acoustic measures, the CPPS and the GNE, were both strongly associated with perceptions of breathiness and were able to discriminate breathiness from hoarseness with good confidence.
Enthalten in den Sammlungen:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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