Jeffrey darma

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Differences between models and in relation to participant factors will be tested using the general linear model. Abstract A reliable and valid automated system for quantifying human affective behavior in ecologically important naturalistic environments would be a transformational tool for research and clinical practice. To ensure generalizability, we further will train and test between independent databases as well.

Jeffrey darma


The models will be trained in three separate databases of dyadic and triadic interaction tasks from over adolescent and adult participants from the US and Australia. Relevance For behavioral science, automated coding of affective behavior from multimodal visual, acoustic, and verbal input will provide researchers with powerful tools to examine basic questions in emotion, psychopathology, and interpersonal processes. In the proposed project, we extend current capabilities in automated multimodal measurement of affective behavior visual, acoustic, and verbal to develop and validate an automated system for detecting the constructs of Positive, Aggressive, and Dysphoric behavior and component lower-level affective behaviors and verbal content.

Jeffrey darma

Jeffrey darma

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5 thoughts on “Jeffrey darma”

  1. Gardaktilar

    Achieving these goals will provide behavioral science with powerful tools to examine basic questions in emotion, psychopathology, and interpersonal processes; and clinicians to improve assessment and ability to track change in clinical and interpersonal functioning over time. To ensure generalizability, we further will train and test between independent databases as well.

    Arashizragore

    The system is based on the manual Living in Family Environments Coding System that has yielded critical findings related to developmental psychopathology and interpersonal processes in depression and other disorders. More generally, automated measurement would contribute to advances in intelligent tutors in education, training in social skills and persuasion in counseling, and affective computing more broadly.

    To ensure generalizability, we further will train and test between independent databases as well.

    In the proposed project, we extend current capabilities in automated multimodal measurement of affective behavior visual, acoustic, and verbal to develop and validate an automated system for detecting the constructs of Positive, Aggressive, and Dysphoric behavior and component lower-level affective behaviors and verbal content.

    Intersystem reliability with manual coding will be evaluated using k-fold cross-validation for both momentary and session level summary scores.

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