A Human Speech-based Behavior Model for Social Robots based on Parent-Child Interaction Therapy

Abstract

Maintaining a healthy parent-child relationship in a family is paramount and has a significant effect on the mental well-being and development of children. One way for improving parent-child communication and relationship is the Parent- Child Interaction Therapy (PCIT), which is a well established therapy method for preschool children and their parents, and has proven to be highly successful. Employing PCIT requires well trained and certified therapist personnel, and a specially constructed therapy room. These requirements make it hard to adopt and practice PCIT for families who could profit from the therapy. In order to help to spread this successful therapy to more children and their parents, we propose a therapy robot system to aid those already taking part in the therapy. This way they can perform the therapy interaction tasks in their homes more effectively and without direct therapist supervision. The proposed system listens to the conversation between the child and parent, and based on the Dyadic Parent-Child Interaction Coding System (DPICS), gives appropriate reactions, so the parent receives feedback whether the interaction is going well or not, thus potentially improving the interaction between parent and child. This system uses Natural Language Processing and Understanding for extracting the necessary information from speech to drive a fuzzy automaton-based behavior model optionally attached to interfaces of social robots. We believe that in the near future, such robot system can improve the efficiency of the independent home users and can also reduce the burden on the therapist personnel. Furthermore, the proposed therapy assisting social robot system can be adopted outside parent-child interaction in the future, e.g. in elderly care for improving caregiver-patient interaction.