Automatic Identification of Ruptures in Transcribed Psychotherapy Sessions

Adam Tsakalidis, Dana Atzil-Slonim, Asaf Polakovski, Natalie Shapira, Rivka Tuval-Mashiach, Maria Liakata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationComputational Linguistics and Clinical Psychology
Subtitle of host publicationImproving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021
EditorsNazli Goharian, Philip Resnik, Andrew Yates, Molly Ireland, Kate Niederhoffer, Rebecca Resnik
PublisherAssociation for Computational Linguistics (ACL)
Pages122-128
Number of pages7
ISBN (Electronic)9781954085411
StatePublished - 2021
Event7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Virtual, Online
Duration: 11 Jun 2021 → …

Publication series

NameComputational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021

Conference

Conference7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021
CityVirtual, Online
Period11/06/21 → …

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Computer Networks and Communications
  • Speech and Hearing

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