ArticleJournal of nonverbal behavior2020
Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development.
Article in Journal of nonverbal behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From data to discovery: Technology propels speech-language research and theory-building in developmental science.Neuroscience and biobehavioral reviews · 2025Pooled it
- Focused review on artificial intelligence for disease detection in infants.Frontiers in digital health · 2024Review
- Emerging Verbal Functions in Early Infancy: Lessons from Observational and Computational Approaches on Typical Development and Neurodevelopmental Disorders.Advances in neurodevelopmental disorders · 2022Article
- Automatic vocalisation-based detection of fragile X syndrome and Rett syndrome.Scientific reports · 2022Article
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Authors and funding
6 authors.
Funding
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.