Deep learning v psychoterapii: Strojová analýza nahrávek terapeutických sezení

Deep learning in psychotherapy: Machine learning applied on therapeutic session recordings

grant

Psychotherapy process; Feedback-Informed Treatment; Routine Outcome Monitoring; Routine Process Monitoring; Automatic Speech Recognition; Unsupervised Adaptation of Speech Recognition system; Diarization; Natural Language Processing; Machine Learning

Psychotherapy is an expert activity requiring continuous decision-making and continuous evaluation of the course of the psychotherapeutic process by the psychotherapist. In practice, however, psychotherapists suffer from a lack of immediate feedback to support this decision. The project aims to create a tool that enables automated analysis of audio recordings of psychotherapeutic sessions to provide psychotherapists feedback on the course in a short time. The project is designed in cooperation with Brno University of Technology and Masaryk University and is based on technologies of automatic speech recognition, natural language computer processing, machine learning, expert coding of psychotherapeutic process and self-assessment questionnaire methods. Its expected outcome will be software providing psychotherapists with user-friendly and practically beneficial feedback with the potential to improve psychotherapeutic care.

Matějka Pavel, Ing., Ph.D. (UPGM FIT VUT) , research leader
Karafiát Martin, Ing., Ph.D. (UPGM FIT VUT) , team leader
Beneš Karel, Ing. (UPGM FIT VUT)
Burget Lukáš, doc. Ing., Ph.D. (UPGM FIT VUT)
Kašpárek Tomáš, Ing. (CVT FIT VUT)
Kesiraju Santosh (UPGM FIT VUT)
Nehyba Jan, Mgr., Ph.D. (MUNI)
Novotný Ondřej, Ing., Ph.D. (UPGM FIT VUT)
Novotný Tomáš
Sarvaš Marek, Bc. (UPGM FIT VUT)
Žižka Josef, Ing. (UPGM FIT VUT)