Automatic Identification of Ruptures in Transcribed Psychotherapy Sessions
Adam Tsakalidis, Dana Atzil-Slonim, Asaf Polakovski, Natalie Shapira, Rivka Tuval-Mashiach, Maria Liakata
Abstract
We present the first work on automatically capturing alliance rupture in transcribed therapy sessions, trained on the text and self-reported rupture scores from both therapists and clients. Our NLP baseline outperforms a strong majority baseline by a large margin and captures client reported ruptures unidentified by therapists in 40% of such cases.- Anthology ID:
- 2021.clpsych-1.15
- Volume:
- Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Nazli Goharian, Philip Resnik, Andrew Yates, Molly Ireland, Kate Niederhoffer, Rebecca Resnik
- Venue:
- CLPsych
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 122–128
- Language:
- URL:
- https://aclanthology.org/2021.clpsych-1.15
- DOI:
- 10.18653/v1/2021.clpsych-1.15
- Cite (ACL):
- Adam Tsakalidis, Dana Atzil-Slonim, Asaf Polakovski, Natalie Shapira, Rivka Tuval-Mashiach, and Maria Liakata. 2021. Automatic Identification of Ruptures in Transcribed Psychotherapy Sessions. In Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access, pages 122–128, Online. Association for Computational Linguistics.
- Cite (Informal):
- Automatic Identification of Ruptures in Transcribed Psychotherapy Sessions (Tsakalidis et al., CLPsych 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.clpsych-1.15.pdf