Speech rhythm auto-recurrence is negatively linked to quality of mental-health counseling interactions

Vera Kempe, Mark A. Adams, George Lovell, Janet McLean, Kate Smith

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We explored use of Recurrence Quantification Analysis (RQA) of speech rhythm data from mental-health counseling sessions for prediction of quality of psychotherapy. Time-series of inter-syllable intervals (ISIs) were extracted from 239 counseling sessions conducted by 12 therapists who repeatedly interacted with 30 clients. We found a negative association between recurrence metrics and client-rated session quality and a negative link between percent of laminarity and therapist-rated session quality, after controlling for self-reported client depression and distress measures and duration of speech sound within a session. Placing value on reduced recurrence in patterns of ISIs, and especially reduced degree of a dyadic system remaining in the same speech-rhythm pattern may be indicative of a desire for variation in content and strategies of client-therapist interaction. These exploratory findings point to the possibility of RQA-based automated systems to capture the ‘footprint’ of the non-verbal dynamic that is indicative of successful mental-health counseling.
Original languageEnglish
Pages (from-to)803-809
Number of pages7
JournalProceedings of the Annual Meeting of the Cognitive Science Society
Issue number44
Publication statusPublished - 1 Jun 2022
Event44th Annual Meeting of the Cognitive Science Society: Cognitive diversity - Metro Toronto Convention Centre, Toronto, Canada
Duration: 27 Jul 202230 Jul 2022
Conference number: 44th


  • Recurrence Qualification Analysis
  • Non-verbal speech parameters
  • Speech rhythm
  • Dialogue
  • Psychotherapy


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