The goal of our study is to reveal acoustic features of speech and elements of nonverbal behavior in “mother-child” dyads during the interaction situation. Participants in the study were 43 dyads “mother-child” with typically developing (TD) children (n = 29 dyads) and children with autism spectrum disorders (ASD, F84 according to ICD-10) (n = 14 dyads), aged 4−7 years. The strategies of mother’s speech behavior leading to the progress of the speech development of TD children are defined. It is shown that mothers of children with ASD adapt their speech to the level of the child’s speech development and are guided by the severity of autistic disorders of the child, but this strategy does not always lead to progress in the child’s speech development. Mother’s speech (MS) behavior to a greater extent provides progress in the ASD child’s nonverbal response and the complication of the grammar level of speech, but not phonetics. The obtained data on the MS characteristics and speech features of children can be used to create a stimulus for computer training programs for children with atypical development.

Original languageEnglish
Title of host publicationSpeech and Computer - 20th International Conference, SPECOM 2018, Proceedings
EditorsRodmonga Potapova, Oliver Jokisch, Alexey Karpov
PublisherSpringer Nature
Pages347-356
Number of pages10
ISBN (Print)9783319995786
DOIs
StatePublished - 1 Sep 2018
Event20th International Conference on Speech and Computer - Leipzig, Germany
Duration: 18 Sep 201822 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11096 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Speech and Computer
Abbreviated titleSPECOM 2018
Country/TerritoryGermany
CityLeipzig
Period18/09/1822/09/18

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

    Research areas

  • Acoustic data, Autism spectrum disorders, Perception analysis, Speech interaction, “Mother-Child” dyads

ID: 36521157