The goal of the study is to determine the effect of the child’s age and the severity of autistic disorders on the speech features of children with autism spectrum disorders (ASD) aged 13–15 years and the impact of these factors in recognition by adults of the information contained in the child speech. Participants of the study were 10 children with ASD and 107 adults – listeners. The design of the study included: spectrographic, phonetic, linguistic analyses of children’s speech; two series of perceptual experiments with determining the children’s speech intelligibility and children’s state – psychophysiological and emotional via speech. The data on the determining of the articulation clarity, normative intonation, recognition of the psychoneurological state and the emotional state of children via speech, and the acoustic features of the speech material are presented. The impact of child’s age and severity of ASD on the speech features and the listeners’ responses is shown. The obtained data indicate a complex trajectory of speech development in ASD informants. The future approach of this research will be automatic classification of ASD child state via speech.

Original languageEnglish
Title of host publicationSpeech and Computer - 22nd International Conference, SPECOM 2020, Proceedings
EditorsAlexey Karpov, Rodmonga Potapova
PublisherSpringer Nature
Pages291-303
Number of pages13
ISBN (Print)9783030602758
DOIs
StatePublished - Oct 2020
Event22nd International Conference on Speech and Computer - St. Petersburg, Russia => Online, St. Petersburg, Russian Federation
Duration: 7 Oct 20209 Oct 2020
http://specom.nw.ru/2020/program/SPECOM-ICR2020-Conference-Program-06102020.pdf

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12335 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Speech and Computer
Abbreviated titleSPECOM 2020
Country/TerritoryRussian Federation
CitySt. Petersburg
Period7/10/209/10/20
Internet address

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

    Research areas

  • Acoustic analysis, Autism spectrum disorders, Child age, Gender, Perceptual experiment, Severity of the disease

ID: 70368835