Florian B Pokorny1, Katrin D Bartl-Pokorny2, Christa Einspieler2, Dajie Zhang3, Ralf Vollmann4, Sven Bölte5, Markus Gugatschka2, Björn W Schuller6, Peter B Marschik7. 1. iDN - interdisciplinary Developmental Neuroscience, Department of Phoniatrics, Medical University of Graz, Graz, Austria; Machine Intelligence & Signal Processing group, MMK, Technical University of Munich, Munich, Germany; Brain, Ears & Eyes - Pattern Recognition Initiative, BioTechMed-Graz, Graz, Austria. 2. iDN - interdisciplinary Developmental Neuroscience, Department of Phoniatrics, Medical University of Graz, Graz, Austria. 3. iDN - interdisciplinary Developmental Neuroscience, Department of Phoniatrics, Medical University of Graz, Graz, Austria; Department of Child and Adolescent Psychiatry and Psychotherapy, iDN - interdisciplinary Developmental Neuroscience, University Medical Center Göttingen, Göttingen, Germany. 4. Brain, Ears & Eyes - Pattern Recognition Initiative, BioTechMed-Graz, Graz, Austria; Department of Linguistics, University of Graz, Graz, Austria. 5. Center of Neurodevelopmental Disorders (KIND), Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden; Child and Adolescent Psychiatry, Center for Psychiatry Research, Stockholm County Council, Sweden. 6. Chair of Embedded Intelligence for Health Care and Wellbeing, Augsburg University, Augsburg, Germany; Group on Language, Audio & Music (GLAM), Department of Computing, Imperial College London, London, UK. 7. iDN - interdisciplinary Developmental Neuroscience, Department of Phoniatrics, Medical University of Graz, Graz, Austria; Brain, Ears & Eyes - Pattern Recognition Initiative, BioTechMed-Graz, Graz, Austria; Department of Child and Adolescent Psychiatry and Psychotherapy, iDN - interdisciplinary Developmental Neuroscience, University Medical Center Göttingen, Göttingen, Germany; Center of Neurodevelopmental Disorders (KIND), Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden. Electronic address: peter.marschik@medunigraz.at.
Abstract
BACKGROUND: Early speech-language development of individuals with Rett syndrome (RTT) has been repeatedly characterised by a co-occurrence of apparently typical and atypical vocalisations. AIMS: To describe specific features of this intermittent character of typical versus atypical early RTT-associated vocalisations by combining auditory Gestalt perception and acoustic vocalisation analysis. METHODS AND PROCEDURES: We extracted N = 363 (pre-)linguistic vocalisations from home video recordings of an infant later diagnosed with RTT. In a listening experiment, all vocalisations were assessed for (a)typicality by five experts on early human development. Listeners' auditory concepts of (a)typicality were investigated in context of a comprehensive set of acoustic time-, spectral- and/or energy-related higher-order features extracted from the vocalisations. OUTCOMES AND RESULTS: More than half of the vocalisations were rated as 'atypical' by at least one listener. Atypicality was mainly related to the auditory attribute 'timbre', and to prosodic, spectral, and voice quality features in the acoustic domain. CONCLUSIONS AND IMPLICATIONS: Knowledge gained in our study shall contribute to the generation of an objective model of early vocalisation atypicality. Such a model might be used for increasing caregivers' and healthcare professionals' sensitivity to identify atypical vocalisation patterns, or even for a probabilistic approach to automatically detect RTT based on early vocalisations.
BACKGROUND: Early speech-language development of individuals with Rett syndrome (RTT) has been repeatedly characterised by a co-occurrence of apparently typical and atypical vocalisations. AIMS: To describe specific features of this intermittent character of typical versus atypical early RTT-associated vocalisations by combining auditory Gestalt perception and acoustic vocalisation analysis. METHODS AND PROCEDURES: We extracted N = 363 (pre-)linguistic vocalisations from home video recordings of an infant later diagnosed with RTT. In a listening experiment, all vocalisations were assessed for (a)typicality by five experts on early human development. Listeners' auditory concepts of (a)typicality were investigated in context of a comprehensive set of acoustic time-, spectral- and/or energy-related higher-order features extracted from the vocalisations. OUTCOMES AND RESULTS: More than half of the vocalisations were rated as 'atypical' by at least one listener. Atypicality was mainly related to the auditory attribute 'timbre', and to prosodic, spectral, and voice quality features in the acoustic domain. CONCLUSIONS AND IMPLICATIONS: Knowledge gained in our study shall contribute to the generation of an objective model of early vocalisation atypicality. Such a model might be used for increasing caregivers' and healthcare professionals' sensitivity to identify atypical vocalisation patterns, or even for a probabilistic approach to automatically detect RTT based on early vocalisations.
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Authors: J L Adrien; P Lenoir; J Martineau; A Perrot; L Hameury; C Larmande; D Sauvage Journal: J Am Acad Child Adolesc Psychiatry Date: 1993-05 Impact factor: 8.829
Authors: Samin A Sajan; Shalini N Jhangiani; Donna M Muzny; Richard A Gibbs; James R Lupski; Daniel G Glaze; Walter E Kaufmann; Steven A Skinner; Fran Annese; Michael J Friez; Jane Lane; Alan K Percy; Jeffrey L Neul Journal: Genet Med Date: 2016-05-12 Impact factor: 8.822
Authors: Sigrun Lang; Katrin D Bartl-Pokorny; Florian B Pokorny; Dunia Garrido; Nivedita Mani; Annette V Fox-Boyer; Dajie Zhang; Peter B Marschik Journal: Curr Dev Disord Rep Date: 2019-05-30
Authors: Florian B Pokorny; Maximilian Schmitt; Mathias Egger; Katrin D Bartl-Pokorny; Dajie Zhang; Björn W Schuller; Peter B Marschik Journal: Sci Rep Date: 2022-08-03 Impact factor: 4.996