Abstract
Objective: We explore state of the art machine learning based tools for automatic facial and linguistic affect analysis to allow easier, faster, and more precise quantification and annotation of children’s verbal and non-verbal affective expressions in psychodynamic child psychotherapy. Method: The sample included 53 Turkish children: 41 with internalizing, externalizing
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