Nonverbal Vocalizations as Speech: Characterizing Natural-Environment Audio from Nonverbal Individuals with Autism

  • Jaya Narain Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Kristina T. Johnson Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Amanda O’Brien Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Peter Wofford Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Pattie Maes Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Rosalind Picard Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

Abstract

The study of nonverbal vocalizations, such as sighs, grunts, and monosyllabic sounds, has largely revolved around the social and affective implications of these sounds within typical speech. However, for individuals who do not use any traditional speech, including those with non- or minimally verbal (nv/mv) autism, these vocalizations contain important, individual-specific affective and communicative information. This paper outlines the methodology, analysis, and technology to investigate the production, perception, and meaning of nonverbal vocalizations from nv/mv individuals in natural environments. We are developing novel signal processing and machine learning methods that will help enable augmentative communication technology, and we are producing a nonverbal vocalization dataset for public release. We hope this work will expand the scientific understanding of these exceptional individuals’ language development and the field of communication more generally.

Published
2020-10-09