Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Pokorny, FB; Bartl-Pokorny, KD; Zhang, DJ; Marschik, PB; Schuller, D; Schuller, BW.
Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development.
J NONVERBAL BEHAV. 2020;
Doi: 10.1007/s10919-020-00332-4
[OPEN ACCESS]
Web of Science
PubMed
FullText
FullText_MUG
- Führende Autor*innen der Med Uni Graz
- Pokorny Florian
- Co-Autor*innen der Med Uni Graz
- Bartl-Pokorny Katrin Daniela
- Marschik Dajie
- Marschik Peter
- Altmetrics:
- Dimensions Citations:
- Plum Analytics:
- Scite (citation analytics):
- Abstract:
- 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.
- Find related publications in this database (Keywords)
- Preverbal development
- Data collection
- Data representation
- Infancy
- Developmental disorders
- Intelligent audio analysis