Parent and Child Voice Activity Detection in Pivotal Response Treatment Video Probes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Training parents, and other primary caregivers, in pivotal response treatment (PRT) has been shown to help children with autism increase their communication skills. This is most effective when the parent maintains a high degree of fidelity to the PRT methodology. Evaluation of a parent’s implementation is currently limited to manual review of PRT sessions by a trained clinician. This process is time consuming and limited in the amount of feedback that can be provided. It also makes long term support for parents who have undergone training difficult. Providing automated data extraction and analysis would alleviate the costs of providing feedback to parents. Since vocal communication is of the most common target skills for PRT implementation, audio analysis is critical to a successful feedback system. Speech patterns in PRT sessions are atypical to common speech that provide a change for audio analysis systems. Adults involved in the treatment often use child-directed language and over exaggerated exclamations as a means of engaging the child. Child speech recognition is a difficult problem that is compounded when children have limited vocal expression. Additionally, PRT sessions depict joint play activities, often producing loud, sustained noise. To address these challenges, audio classification techniques were explored to determine a methodology for labeling audio segments in videos of PRT sessions. By implementing separate support vector machine (SVM) implementations for speech activity, and speaker separation, an average accuracy of 79% was achieved.

Original languageEnglish (US)
Title of host publicationLearning and Collaboration Technologies. Ubiquitous and Virtual Environments for Learning and Collaboration - 6th International Conference, LCT 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
EditorsPanayiotis Zaphiris, Andri Ioannou
PublisherSpringer Verlag
Pages270-286
Number of pages17
ISBN (Print)9783030218164
DOIs
StatePublished - Jan 1 2019
Event6th International Conference on Learning and Collaboration Technologies, LCT 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States
Duration: Jul 26 2019Jul 31 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11591 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Learning and Collaboration Technologies, LCT 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
CountryUnited States
CityOrlando
Period7/26/197/31/19

Keywords

  • Autism spectrum disorder
  • Child speech detection
  • Dyadic audio analysis
  • Pivotal response treatment
  • Speaker separation
  • Vocal activity detection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Heath, C. D. C., McDaniel, T., Venkateswara, H., & Panchanathan, S. (2019). Parent and Child Voice Activity Detection in Pivotal Response Treatment Video Probes. In P. Zaphiris, & A. Ioannou (Eds.), Learning and Collaboration Technologies. Ubiquitous and Virtual Environments for Learning and Collaboration - 6th International Conference, LCT 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings (pp. 270-286). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11591 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-21817-1_21