Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development.
Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child's first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically clas...
| Publicado en: | Journal of Nonverbal Behavior Vol. 44; no. 4; pp. 419 - 437 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2020
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=146478603&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 146478603 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 01915886 JNV jtl: Journal of Nonverbal Behavior issn: 01915886 maglogo: N pubinfo: dt: Dec2020 vid: 44 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 146478603 10.1007/s10919-020-00332-4 ppf: 419 ppct: 18 formats: fmt: – @attributes: type: T – @attributes: type: P size: 722KB tig: atl: Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development. aug: au: Pokorny, Florian B. Bartl-Pokorny, Katrin D. Zhang, Dajie Marschik, Peter B. Schuller, Dagmar Schuller, Björn W. affil: iDN – interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria Machine Intelligence & Signal Processing group (MISP), Chair of Human–Machine Communication, Technical University of Munich, Munich, Germany Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany Leibniz ScienceCampus Primate Cognition, Göttingen, Germany Center of Neurodevelopmental Disorders (KIND), Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden audEERING GmbH, Gilching, Germany ZD.B Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany GLAM – Group on Language, Audio & Music, Department of Computing, Imperial College London, London, UK su: Autism Child development Developmental disabilities Language acquisition Machine learning Rett syndrome Data analysis Content mining sug: subj: Autism Child development Developmental disabilities Language acquisition Machine learning Rett syndrome Data analysis Content mining keyword: Data collection Data representation Developmental disorders Infancy Intelligent audio analysis Preverbal development Data collection Data representation Developmental disorders Infancy Intelligent audio analysis Preverbal development ab: Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child's first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically classified and acoustically characterized. More recently, specific preverbal phenomena were discussed to play a role as early indicators of atypical development. Recent advancements in audio signal processing and machine learning have allowed for novel approaches in preverbal behavior analysis including automatic vocalization-based differentiation of typically and atypically developing individuals. In this paper, we give a methodological overview of current strategies for collecting and acoustically representing preverbal data for intelligent audio analysis paradigms. Efficiency in the context of data collection and data representation is discussed. Following current research trends, we set a special focus on challenges that arise when dealing with preverbal data of individuals with late detected developmental disorders, such as autism spectrum disorder or Rett syndrome. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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