We present the TherapyView, a demonstration system to help therapists visualize the dynamic contents of past treatment sessions, enabled by the state-of-the-art neural topic modeling techniques to analyze the topical tendencies of various psychiatric conditions and deep learning-based image generation engine to provide a visual summary. The system incorporates temporal modeling to provide a time-series representation of topic similarities at a turn-level resolution and AI-generated artworks given the dialogue segments to provide a concise representations of the contents covered in the session, offering interpretable insights for therapists to optimize their strategies and enhance the effectiveness of psychotherapy. This system provides a proof of concept of AI-augmented therapy tools with e in-depth understanding of the patient's mental state and enabling more effective treatment.
@article{arxiv.2302.10845,
title = {TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts},
author = {Baihan Lin and Stefan Zecevic and Djallel Bouneffouf and Guillermo Cecchi},
journal= {arXiv preprint arXiv:2302.10845},
year = {2023}
}
Comments
This work extends our prior empirical work on topic modeling (arxiv:2204.10189) to now provide an interpretable and interactive data visualization platform with AI-generated artworks as a concrete user scenario for therapists