How Autism Affects Speech Understanding in Multitalker Environments

Abstract

The modern household can be a chaotic place, full of noise from radios, televisions, family members. The ability to separate speech from background noise is a critical skill for understanding spoken language in such environments. Recent studies suggest that adults with Autism Spectrum Disorders have particular difficulty recognizing speech in acoustically-hostile environments (e.g., Alcantara et al. 2004), but an underlying cause for this deficit remains unknown. This proposal tests our hypotheses that children with ASD will find it more difficult to separate the speech of different talkers than do their typically-developing peers. We also predict that they will fail to exploit visual cues on a talkers face to help in this task, further limiting their ability to process input and learn language on a typical schedule. We are still analyzing the data we have collected, but preliminary analyses suggest that while children with ASD and typically developing children appear better able to recognize speech in quiet than in noise, the children with ASD are not specifically impaired in the noisy condition. Rather, the children with ASD performed more poorly than language-matched TD children in both quiet and noisy conditions, suggesting a more global difficulty in speech recognition.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2015
Accession Number
AD1005074

Entities

People

  • Elizabeth Redcay
  • Nan Ratner
  • Rochelle S. Newman

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Autism
  • Automated Speech Recognition
  • Background Noise
  • Computer Programming
  • Diseases And Disorders
  • Environment
  • Families (Human)
  • Identification
  • Language
  • Noise
  • Professional Development
  • Psychiatry
  • Psychology
  • Recognition
  • Spectra
  • Students
  • Training

Readers

  • Child and Adolescent Substance Abuse Science in Autism Spectrum Disorders.
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks