Automated segmentation of child-clinician speech in naturalistic clinical contexts.

Journal: Research in developmental disabilities
PMID: 39827718

Abstract

BACKGROUND: Computational approaches hold significant promise for enhancing diagnosis and therapy in child and adolescent clinical practice. Clinical procedures heavily depend n vocal exchanges and interpersonal dynamics conveyed through speech. Research highlights the importance of investigating acoustic features and dyadic interactions during child development. However, observational methods are labor-intensive, time-consuming, and suffer from limited objectivity and quantification, hindering translation to everyday care.

Authors

  • Giulio Bertamini
    Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière University Hospital - Sorbonne University, 47-83 Bd de l'Hôpital, Paris, Île-de-France 75013, France; Laboratory of Observation, Diagnosis, and Education, Department of Psychology and Cognitive Science - University of Trento, Via Matteo del Ben, 5B, Rovereto, TN 38068, Italy; Institute of Intelligent Systems and Robotics, Sorbonne University, Pyramide - T55, 4 Pl. Jussieu 65, Paris, Île-de-France 75005, France. Electronic address: giulio.bertamini@unitn.it.
  • Cesare Furlanello
    a Fondazione Bruno Kessler , Trento , Italy.
  • Mohamed Chetouani
    Laboratoire ISIR, Université UPMC, CNRS, 75005 Paris, France.
  • David Cohen
    Laboratoire ISIR, Université UPMC, CNRS, 75005 Paris, France.
  • Paola Venuti
    Laboratory of Observation, Diagnosis, and Education, Department of Psychology and Cognitive Science - University of Trento, Via Matteo del Ben, 5B, Rovereto, TN 38068, Italy. Electronic address: paola.venuti@unitn.it.

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