Towards an artificial therapy assistant: Measuring excessive stress from speech

Frans van der Sluis, Egon van den Broek, Ton Dijkstra

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    Abstract

    The measurement of (excessive) stress is still a challenging endeavor. Most tools rely on either introspection or expert opinion and are, therefore, often less reliable or a burden on the patient. An objective method could relieve these problems and, consequently, assist diagnostics. Speech was considered an excellent candidate for an objective, unobtrusive measure of emotion. True stress was successfully induced, using two storytelling sessions performed by 25 patients suffering from a stress disorder. When reading either a happy or a sad story, different stress levels were reported using the Subjective Unit of Distress (SUD). A linear regression model consisting of the high-frequency energy, pitch, and zero crossings of the speech signal was able to explain 70% of the variance in the subjectively reported stress. The results demonstrate the feasibility of an objective measurement of stress in speech. As such, the foundation for an Artificial Therapeutic Agent is laid, capable of assisting therapists through an objective measurement of experienced stress.
    Original languageUndefined
    Title of host publicationProceedings of the International Conference on Health Informatics, HealthInf 2011
    EditorsV. Traver, A. Fred, J. Filipe, H. Gamboa
    Place of PublicationPortugal
    PublisherINSTICC PRESS
    Pages357-363
    Number of pages7
    ISBN (Print)978-989-8425-34-8
    Publication statusPublished - 26 Jan 2011
    EventInternational Conference on Health Informatics, Healthinf 2011 - Rome, Italy
    Duration: 26 Jan 201129 Jan 2011

    Publication series

    Name
    PublisherINSTICC Press

    Conference

    ConferenceInternational Conference on Health Informatics, Healthinf 2011
    Period26/01/1129/01/11
    Other26-29 Jan 2011

    Keywords

    • METIS-277522
    • IR-75881
    • Model
    • Agent
    • Stress
    • HMI-HF: Human Factors
    • Psychiatry
    • Diagnosis
    • EWI-19527
    • HMI-SLT: Speech and Language Technology
    • Speech

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